generated by bibbase.org
  2025 (3)
Adaptive ensemble optimization for memory-related hyperparameters in retraining DNN at edge. Xu, Y.; Han, R.; Zuo, X.; Ouyang, J.; Liu, C. H.; and Chen, L. Y. Future Gener. Comput. Syst., 164: 107600. 2025.
Adaptive ensemble optimization for memory-related hyperparameters in retraining DNN at edge [link]Paper   doi   link   bibtex  
EdgeTA: Neuron-Grained Scaling of Foundation Models in Edge-Side Retraining. Zhang, Q.; Han, R.; Liu, C. H.; Wang, G.; Guo, S.; and Chen, L. Y. IEEE Trans. Mob. Comput., 24(4): 2690–2707. 2025.
EdgeTA: Neuron-Grained Scaling of Foundation Models in Edge-Side Retraining [link]Paper   doi   link   bibtex  
SkipPipe: Partial and Reordered Pipelining Framework for Training LLMs in Heterogeneous Networks. Blagoev, N.; Chen, L. Y.; and Ersoy, O. CoRR, abs/2502.19913. 2025.
SkipPipe: Partial and Reordered Pipelining Framework for Training LLMs in Heterogeneous Networks [link]Paper   doi   link   bibtex  
  2024 (30)
RobustDA: Lightweight Robust Domain Adaptation for Evolving Data at Edge. Guo, X.; Zuo, X.; Han, R.; Ouyang, J.; Xie, J.; Liu, C. H.; Zhang, Q.; Guo, Y.; Chen, J.; and Chen, L. Y. IEEE J. Emerg. Sel. Topics Circuits Syst., 14(4): 688–704. 2024.
RobustDA: Lightweight Robust Domain Adaptation for Evolving Data at Edge [link]Paper   doi   link   bibtex  
CTAB-GAN+: enhancing tabular data synthesis. Zhao, Z.; Kunar, A.; Birke, R.; der Scheer, H. V.; and Chen, L. Y. Frontiers Big Data, 6. 2024.
CTAB-GAN+: enhancing tabular data synthesis [link]Paper   doi   link   bibtex  
FedViT: Federated continual learning of vision transformer at edge. Zuo, X.; Luopan, Y.; Han, R.; Zhang, Q.; Liu, C. H.; Wang, G.; and Chen, L. Y. Future Gener. Comput. Syst., 154: 1–15. 2024.
FedViT: Federated continual learning of vision transformer at edge [link]Paper   doi   link   bibtex  
ElasticDNN: On-Device Neural Network Remodeling for Adapting Evolving Vision Domains at Edge. Zhang, Q.; Han, R.; Liu, C. H.; Wang, G.; and Chen, L. Y. IEEE Trans. Computers, 73(6): 1616–1630. 2024.
ElasticDNN: On-Device Neural Network Remodeling for Adapting Evolving Vision Domains at Edge [link]Paper   doi   link   bibtex  
Amalur: The Convergence of Data Integration and Machine Learning. Li, Z.; Sun, W.; Zhan, D.; Kang, Y.; Chen, L. Y.; Bozzon, A.; and Hai, R. IEEE Trans. Knowl. Data Eng., 36(12): 7353–7367. 2024.
Amalur: The Convergence of Data Integration and Machine Learning [link]Paper   doi   link   bibtex  
Duwak: Dual Watermarks in Large Language Models. Zhu, C.; Galjaard, J.; Chen, P.; and Chen, L. Y. In Ku, L.; Martins, A.; and Srikumar, V., editor(s), Findings of the Association for Computational Linguistics, ACL 2024, Bangkok, Thailand and virtual meeting, August 11-16, 2024, pages 11416–11436, 2024. Association for Computational Linguistics
Duwak: Dual Watermarks in Large Language Models [link]Paper   doi   link   bibtex  
Trustworthy Federated Learning Systems. Chen, L. Y. In van Steen, M.; and Pahl, C., editor(s), Proceedings of the 14th International Conference on Cloud Computing and Services Science, CLOSER 2024, Angers, France, May 2-4, 2024, pages 7, 2024. SCITEPRESS
link   bibtex  
S i 1 o F use: Cross-silo Synthetic Data Generation with Latent Tabular Diffusion Models. Shankar, A.; Brouwer, H.; Hai, R.; and Chen, L. Y. In 40th IEEE International Conference on Data Engineering, ICDE 2024, Utrecht, The Netherlands, May 13-16, 2024, pages 110–123, 2024. IEEE
S i 1 o F use: Cross-silo Synthetic Data Generation with Latent Tabular Diffusion Models [link]Paper   doi   link   bibtex  
Spyker: Asynchronous Multi-Server Federated Learning for Geo-Distributed Clients. Zuo, Y.; Cox, B.; Chen, L. Y.; and Decouchant, J. In Cao, J.; Jin, Z.; Schiavoni, V.; and Edinger, J., editor(s), Proceedings of the 25th International Middleware Conference, MIDDLEWARE 2024, Hong Kong, SAR, China, December 2-6, 2024, pages 367–378, 2024. ACM
Spyker: Asynchronous Multi-Server Federated Learning for Geo-Distributed Clients [link]Paper   doi   link   bibtex  
On Dark Knowledge for Distilling Generators. Hong, C.; Birke, R.; Chen, P.; and Chen, L. Y. In Yang, D.; Xie, X.; Tseng, V. S.; Pei, J.; Huang, J.; and Lin, J. C., editor(s), Advances in Knowledge Discovery and Data Mining - 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7-10, 2024, Proceedings, Part II, volume 14646, of Lecture Notes in Computer Science, pages 235–247, 2024. Springer
On Dark Knowledge for Distilling Generators [link]Paper   doi   link   bibtex  
DALLMi: Domain Adaption for LLM-Based Multi-label Classifier. Betianu, M.; Malan, A.; Aldinucci, M.; Birke, R.; and Chen, L. Y. In Yang, D.; Xie, X.; Tseng, V. S.; Pei, J.; Huang, J.; and Lin, J. C., editor(s), Advances in Knowledge Discovery and Data Mining - 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7-10, 2024, Proceedings, Part III, volume 14647, of Lecture Notes in Computer Science, pages 277–289, 2024. Springer
DALLMi: Domain Adaption for LLM-Based Multi-label Classifier [link]Paper   doi   link   bibtex  
TabVFL: Improving Latent Representation in Vertical Federated Learning. Rashad, M.; Zhao, Z.; Decouchant, J.; and Chen, L. Y. In 43rd International Symposium on Reliable Distributed Systems, SRDS 2024, Charlotte, NC, USA, September 30 - Oct. 3, 2024, pages 210–221, 2024. IEEE
TabVFL: Improving Latent Representation in Vertical Federated Learning [link]Paper   doi   link   bibtex  
On Quantifying the Gradient Inversion Risk of Data Reuse in Federated Learning Systems. Huang, J.; Chen, L. Y.; and Roos, S. In 43rd International Symposium on Reliable Distributed Systems, SRDS 2024, Charlotte, NC, USA, September 30 - Oct. 3, 2024, pages 235–247, 2024. IEEE
On Quantifying the Gradient Inversion Risk of Data Reuse in Federated Learning Systems [link]Paper   doi   link   bibtex  
CLUES: Collusive Theft of Conditional Generative Adversarial Networks. Queyrut, S.; Schiavoni, V.; Chen, L. Y.; Felber, P.; and Birke, R. In 43rd International Symposium on Reliable Distributed Systems, SRDS 2024, Charlotte, NC, USA, September 30 - Oct. 3, 2024, pages 282–293, 2024. IEEE
CLUES: Collusive Theft of Conditional Generative Adversarial Networks [link]Paper   doi   link   bibtex  
The Rise of Diffusion Models in Time-Series Forecasting. Meijer, C.; and Chen, L. Y. CoRR, abs/2401.03006. 2024.
The Rise of Diffusion Models in Time-Series Forecasting [link]Paper   doi   link   bibtex  
Quantifying and Mitigating Privacy Risks for Tabular Generative Models. Zhu, C.; Tang, J.; Brouwer, H.; Pérez, J. F.; van Dijk, M.; and Chen, L. Y. CoRR, abs/2403.07842. 2024.
Quantifying and Mitigating Privacy Risks for Tabular Generative Models [link]Paper   doi   link   bibtex  
Duwak: Dual Watermarks in Large Language Models. Zhu, C.; Galjaard, J.; Chen, P.; and Chen, L. Y. CoRR, abs/2403.13000. 2024.
Duwak: Dual Watermarks in Large Language Models [link]Paper   doi   link   bibtex  
SiloFuse: Cross-silo Synthetic Data Generation with Latent Tabular Diffusion Models. Shankar, A.; Brouwer, H.; Hai, R.; and Chen, L. Y. CoRR, abs/2404.03299. 2024.
SiloFuse: Cross-silo Synthetic Data Generation with Latent Tabular Diffusion Models [link]Paper   doi   link   bibtex  
TabVFL: Improving Latent Representation in Vertical Federated Learning. Rashad, M.; Zhao, Z.; Decouchant, J.; and Chen, L. Y. CoRR, abs/2404.17990. 2024.
TabVFL: Improving Latent Representation in Vertical Federated Learning [link]Paper   doi   link   bibtex  
DALLMi: Domain Adaption for LLM-based Multi-label Classifier. Betianu, M.; Malan, A.; Aldinucci, M.; Birke, R.; and Chen, L. Y. CoRR, abs/2405.01883. 2024.
DALLMi: Domain Adaption for LLM-based Multi-label Classifier [link]Paper   doi   link   bibtex  
SFDDM: Single-fold Distillation for Diffusion models. Hong, C.; Huang, J.; Birke, R.; Epema, D. H. J.; Roos, S.; and Chen, L. Y. CoRR, abs/2405.14961. 2024.
SFDDM: Single-fold Distillation for Diffusion models [link]Paper   doi   link   bibtex  
CCBNet: Confidential Collaborative Bayesian Networks Inference. Malan, A.; Decouchant, J.; Guzella, T.; and Chen, L. Y. CoRR, abs/2405.15055. 2024.
CCBNet: Confidential Collaborative Bayesian Networks Inference [link]Paper   doi   link   bibtex  
Gradient Inversion of Federated Diffusion Models. Huang, J.; Hong, C.; Chen, L. Y.; and Roos, S. CoRR, abs/2405.20380. 2024.
Gradient Inversion of Federated Diffusion Models [link]Paper   doi   link   bibtex  
Share Your Secrets for Privacy! Confidential Forecasting with Vertical Federated Learning. Shankar, A.; Chen, L. Y.; Decouchant, J.; Gkorou, D.; and Hai, R. CoRR, abs/2405.20761. 2024.
Share Your Secrets for Privacy! Confidential Forecasting with Vertical Federated Learning [link]Paper   doi   link   bibtex  
Asynchronous Byzantine Federated Learning. Cox, B.; Malan, A.; Chen, L. Y.; and Decouchant, J. CoRR, abs/2406.01438. 2024.
Asynchronous Byzantine Federated Learning [link]Paper   doi   link   bibtex  
Asynchronous Multi-Server Federated Learning for Geo-Distributed Clients. Zuo, Y.; Cox, B.; Chen, L. Y.; and Decouchant, J. CoRR, abs/2406.01439. 2024.
Asynchronous Multi-Server Federated Learning for Geo-Distributed Clients [link]Paper   doi   link   bibtex  
Parameterizing Federated Continual Learning for Reproducible Research. Cox, B.; Galjaard, J.; Shankar, A.; Decouchant, J.; and Chen, L. Y. CoRR, abs/2406.02015. 2024.
Parameterizing Federated Continual Learning for Reproducible Research [link]Paper   doi   link   bibtex  
Federated Time Series Generation on Feature and Temporally Misaligned Data. Fan, C.; Soi, Z. W.; Shankar, A.; Malan, A.; and Chen, L. Y. CoRR, abs/2410.21072. 2024.
Federated Time Series Generation on Feature and Temporally Misaligned Data [link]Paper   doi   link   bibtex  
MPQ-Diff: Mixed Precision Quantization for Diffusion Models. Maruzzelli, R. M.; Lewandowski, B.; and Chen, L. Y. CoRR, abs/2412.00144. 2024.
MPQ-Diff: Mixed Precision Quantization for Diffusion Models [link]Paper   doi   link   bibtex  
Multigraph Message Passing with Bi-Directional Multi-Edge Aggregations. Bilgi, H. Ç.; Chen, L. Y.; and Atasu, K. CoRR, abs/2412.00241. 2024.
Multigraph Message Passing with Bi-Directional Multi-Edge Aggregations [link]Paper   doi   link   bibtex  
  2023 (17)
Fast DRL-based scheduler configuration tuning for reducing tail latency in edge-cloud jobs. Wen, S.; Han, R.; Liu, C. H.; and Chen, L. Y. J. Cloud Comput., 12(1): 90. 2023.
Fast DRL-based scheduler configuration tuning for reducing tail latency in edge-cloud jobs [link]Paper   doi   link   bibtex  
GDTS: GAN-Based Distributed Tabular Synthesizer. Zhao, Z.; Birke, R.; and Chen, L. Y. In 16th IEEE International Conference on Cloud Computing, CLOUD 2023, Chicago, IL, USA, July 2-8, 2023, pages 570–576, 2023. IEEE
GDTS: GAN-Based Distributed Tabular Synthesizer [link]Paper   doi   link   bibtex  
FCT-GAN: Enhancing Global Correlation of Table Synthesis via Fourier Transform. Zhao, Z.; Birke, R.; and Chen, L. Y. In Frommholz, I.; Hopfgartner, F.; Lee, M.; Oakes, M.; Lalmas, M.; Zhang, M.; and Santos, R. L. T., editor(s), Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023, pages 4450–4454, 2023. ACM
FCT-GAN: Enhancing Global Correlation of Table Synthesis via Fourier Transform [link]Paper   doi   link   bibtex  
Fabricated Flips: Poisoning Federated Learning without Data. Huang, J.; Zhao, Z.; Chen, L. Y.; and Roos, S. In 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Network, DSN 2023, Porto, Portugal, June 27-30, 2023, pages 274–287, 2023. IEEE
Fabricated Flips: Poisoning Federated Learning without Data [link]Paper   doi   link   bibtex  
Defending Against Free-Riders Attacks in Distributed Generative Adversarial Networks. Zhao, Z.; Huang, J.; Chen, L. Y.; and Roos, S. In Baldimtsi, F.; and Cachin, C., editor(s), Financial Cryptography and Data Security - 27th International Conference, FC 2023, Bol, Brač, Croatia, May 1-5, 2023, Revised Selected Papers, Part II, volume 13951, of Lecture Notes in Computer Science, pages 200–217, 2023. Springer
Defending Against Free-Riders Attacks in Distributed Generative Adversarial Networks [link]Paper   doi   link   bibtex  
FedKNOW: Federated Continual Learning with Signature Task Knowledge Integration at Edge. Luopan, Y.; Han, R.; Zhang, Q.; Liu, C. H.; Wang, G.; and Chen, L. Y. In 39th IEEE International Conference on Data Engineering, ICDE 2023, Anaheim, CA, USA, April 3-7, 2023, pages 341–354, 2023. IEEE
FedKNOW: Federated Continual Learning with Signature Task Knowledge Integration at Edge [link]Paper   doi   link   bibtex  
EdgeVisionBench: A Benchmark of Evolving Input Domains for Vision Applications at Edge. Zhang, Q.; Han, R.; Liu, C. H.; Wang, G.; and Chen, L. Y. In 39th IEEE International Conference on Data Engineering, ICDE 2023, Anaheim, CA, USA, April 3-7, 2023, pages 3643–3646, 2023. IEEE
EdgeVisionBench: A Benchmark of Evolving Input Domains for Vision Applications at Edge [link]Paper   doi   link   bibtex  
LeadFL: Client Self-Defense against Model Poisoning in Federated Learning. Zhu, C.; Roos, S.; and Chen, L. Y. In Krause, A.; Brunskill, E.; Cho, K.; Engelhardt, B.; Sabato, S.; and Scarlett, J., editor(s), International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, volume 202, of Proceedings of Machine Learning Research, pages 43158–43180, 2023. PMLR
LeadFL: Client Self-Defense against Model Poisoning in Federated Learning [link]Paper   link   bibtex  
Characterizing Distributed Machine Learning Workloads on Apache Spark: (Experimentation and Deployment Paper). Djebrouni, Y.; Rocha, I.; Bouchenak, S.; Chen, L. Y.; Felber, P.; Marangozova, V.; and Schiavoni, V. In Proceedings of the 24th International Middleware Conference, Middleware 2023, Bologna, Italy, December 11-15, 2023, pages 151–164, 2023. ACM
Characterizing Distributed Machine Learning Workloads on Apache Spark: (Experimentation and Deployment Paper) [link]Paper   doi   link   bibtex  
Maverick Matters: Client Contribution and Selection in Federated Learning. Huang, J.; Hong, C.; Liu, Y.; Chen, L. Y.; and Roos, S. In Kashima, H.; Idé, T.; and Peng, W., editor(s), Advances in Knowledge Discovery and Data Mining - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25-28, 2023, Proceedings, Part II, volume 13936, of Lecture Notes in Computer Science, pages 269–282, 2023. Springer
Maverick Matters: Client Contribution and Selection in Federated Learning [link]Paper   doi   link   bibtex  
Exploring and Exploiting Data-Free Model Stealing. Hong, C.; Huang, J.; Birke, R.; and Chen, L. Y. In Koutra, D.; Plant, C.; Rodriguez, M. G.; Baralis, E.; and Bonchi, F., editor(s), Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part V, volume 14173, of Lecture Notes in Computer Science, pages 20–35, 2023. Springer
Exploring and Exploiting Data-Free Model Stealing [link]Paper   doi   link   bibtex  
Parameterizing Federated Continual Learning for Reproducible Research. Cox, B.; Galjaard, J.; Shankar, A.; Decouchant, J.; and Chen, L. Y. In Meo, R.; and Silvestri, F., editor(s), Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Revised Selected Papers, Part V, volume 2137, of Communications in Computer and Information Science, pages 478–486, 2023. Springer
Parameterizing Federated Continual Learning for Reproducible Research [link]Paper   doi   link   bibtex  
Robust Learning via Golden Symmetric Loss of (un)Trusted Labels. Ghiassi, A.; Birke, R.; and Chen, L. Y. In Shekhar, S.; Zhou, Z.; Chiang, Y.; and Stiglic, G., editor(s), Proceedings of the 2023 SIAM International Conference on Data Mining, SDM 2023, Minneapolis-St. Paul Twin Cities, MN, USA, April 27-29, 2023, pages 568–576, 2023. SIAM
Robust Learning via Golden Symmetric Loss of (un)Trusted Labels [link]Paper   doi   link   bibtex  
GTV: Generating Tabular Data via Vertical Federated Learning. Zhao, Z.; Wu, H.; van Moorsel, A.; and Chen, L. Y. CoRR, abs/2302.01706. 2023.
GTV: Generating Tabular Data via Vertical Federated Learning [link]Paper   doi   link   bibtex  
BatMan-CLR: Making Few-shots Meta-Learners Resilient Against Label Noise. Galjaard, J. M.; Birke, R.; Pérez, J. F.; and Chen, L. Y. CoRR, abs/2309.06046. 2023.
BatMan-CLR: Making Few-shots Meta-Learners Resilient Against Label Noise [link]Paper   doi   link   bibtex  
TabuLa: Harnessing Language Models for Tabular Data Synthesis. Zhao, Z.; Birke, R.; and Chen, L. Y. CoRR, abs/2310.12746. 2023.
TabuLa: Harnessing Language Models for Tabular Data Synthesis [link]Paper   doi   link   bibtex  
CDGraph: Dual Conditional Social Graph Synthesizing via Diffusion Model. Tsai, J.; Teng, Y.; Yew, H. C.; Yang, D.; and Chen, L. Y. CoRR, abs/2311.01729. 2023.
CDGraph: Dual Conditional Social Graph Synthesizing via Diffusion Model [link]Paper   doi   link   bibtex  
  2022 (26)
Memory-aware and context-aware multi-DNN inference on the edge. Cox, B.; Birke, R.; and Chen, L. Y. Pervasive Mob. Comput., 83: 101594. 2022.
Memory-aware and context-aware multi-DNN inference on the edge [link]Paper   doi   link   bibtex  
Multiple Strategies Differential Privacy on Sparse Tensor Factorization for Network Traffic Analysis in 5G. Wang, J.; Han, H.; Li, H.; He, S.; Sharma, P. K.; and Chen, L. Y. IEEE Trans. Ind. Informatics, 18(3): 1939–1948. 2022.
Multiple Strategies Differential Privacy on Sparse Tensor Factorization for Network Traffic Analysis in 5G [link]Paper   doi   link   bibtex  
Lightweight and Accurate DNN-Based Anomaly Detection at Edge. Zhang, Q.; Han, R.; Xin, G.; Liu, C. H.; Wang, G.; and Chen, L. Y. IEEE Trans. Parallel Distributed Syst., 33(11): 2927–2942. 2022.
Lightweight and Accurate DNN-Based Anomaly Detection at Edge [link]Paper   doi   link   bibtex  
Federated Learning With Heterogeneity-Aware Probabilistic Synchronous Parallel on Edge. Zhao, J.; Han, R.; Yang, Y.; Catterall, B.; Liu, C. H.; Chen, L. Y.; Mortier, R.; Crowcroft, J.; and Wang, L. IEEE Trans. Serv. Comput., 15(2): 614–626. 2022.
Federated Learning With Heterogeneity-Aware Probabilistic Synchronous Parallel on Edge [link]Paper   doi   link   bibtex  
Trusted Loss Correction for Noisy Multi-Label Learning. Ghiassi, A.; Pene, C. O.; Birke, R.; and Chen, L. Y. In Balasubramanian, V. N.; and Tsang, I. W., editor(s), Asian Conference on Machine Learning, ACML 2022, 12-14 December 2022, Hyderabad, India, volume 189, of Proceedings of Machine Learning Research, pages 343–358, 2022. PMLR
Trusted Loss Correction for Noisy Multi-Label Learning [link]Paper   link   bibtex  
Multi Label Loss Correction against Missing and Corrupted Labels. Ghiassi, A.; Birke, R.; and Chen, L. Y. In Balasubramanian, V. N.; and Tsang, I. W., editor(s), Asian Conference on Machine Learning, ACML 2022, 12-14 December 2022, Hyderabad, India, volume 189, of Proceedings of Machine Learning Research, pages 359–374, 2022. PMLR
Multi Label Loss Correction against Missing and Corrupted Labels [link]Paper   link   bibtex  
Permutation-Invariant Tabular Data Synthesis. Zhu, Y.; Zhao, Z.; Birke, R.; and Chen, L. Y. In Tsumoto, S.; Ohsawa, Y.; Chen, L.; den Poel, D. V.; Hu, X.; Motomura, Y.; Takagi, T.; Wu, L.; Xie, Y.; Abe, A.; and Raghavan, V., editor(s), IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan, December 17-20, 2022, pages 5855–5864, 2022. IEEE
Permutation-Invariant Tabular Data Synthesis [link]Paper   doi   link   bibtex  
Targeted Influence with Community and Gender-Aware Seeding. Styczen, M.; Chen, B.; Teng, Y.; Pignolet, Y.; Chen, L. Y.; and Yang, D. In Hasan, M. A.; and Xiong, L., editor(s), Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022, pages 4515–4519, 2022. ACM
Targeted Influence with Community and Gender-Aware Seeding [link]Paper   doi   link   bibtex  
LABNET: A Collaborative Method for DNN Training and Label Aggregation. Ghiassi, A.; Birke, R.; and Chen, L. Y. In Rocha, A. P.; Steels, L.; and van den Herik, H. J., editor(s), Proceedings of the 14th International Conference on Agents and Artificial Intelligence, ICAART 2022, Volume 2, Online Streaming, February 3-5, 2022, pages 56–66, 2022. SCITEPRESS
LABNET: A Collaborative Method for DNN Training and Label Aggregation [link]Paper   doi   link   bibtex  
Performance Modeling for Short-Term Cache Allocation. Stewart, C.; Morris, N.; Chen, L. Y.; and Birke, R. In Proceedings of the 51st International Conference on Parallel Processing, ICPP 2022, Bordeaux, France, 29 August 2022 - 1 September 2022, pages 31:1–31:11, 2022. ACM
Performance Modeling for Short-Term Cache Allocation [link]Paper   doi   link   bibtex  
EdgeTuner: Fast Scheduling Algorithm Tuning for Dynamic Edge-Cloud Workloads and Resources. Han, R.; Wen, S.; Liu, C. H.; Yuan, Y.; Wang, G.; and Chen, L. Y. In IEEE INFOCOM 2022 - IEEE Conference on Computer Communications, London, United Kingdom, May 2-5, 2022, pages 880–889, 2022. IEEE
EdgeTuner: Fast Scheduling Algorithm Tuning for Dynamic Edge-Cloud Workloads and Resources [link]Paper   doi   link   bibtex  
Federated Learning for Tabular Data: Exploring Potential Risk to Privacy. Wu, H.; Zhao, Z.; Chen, L. Y.; and van Moorsel, A. In IEEE 33rd International Symposium on Software Reliability Engineering, ISSRE 2022, Charlotte, NC, USA, October 31 - Nov. 3, 2022, pages 193–204, 2022. IEEE
Federated Learning for Tabular Data: Exploring Potential Risk to Privacy [link]Paper   doi   link   bibtex  
EdgeTune: Inference-Aware Multi-Parameter Tuning. Rocha, I.; Felber, P.; Schiavoni, V.; and Chen, L. Y. In Bellavista, P.; Zhang, K.; Gherbi, A.; Bagchi, S.; Patiño, M.; Modica, G. D.; and Gascon-Samson, J., editor(s), Middleware '22: 23rd International Middleware Conference, Quebec, QC, Canada, November 7 - 11, 2022, pages 1–14, 2022. ACM
EdgeTune: Inference-Aware Multi-Parameter Tuning [link]Paper   doi   link   bibtex  
Aergia: leveraging heterogeneity in federated learning systems. Cox, B.; Chen, L. Y.; and Decouchant, J. In Bellavista, P.; Zhang, K.; Gherbi, A.; Bagchi, S.; Patiño, M.; Modica, G. D.; and Gascon-Samson, J., editor(s), Middleware '22: 23rd International Middleware Conference, Quebec, QC, Canada, November 7 - 11, 2022, pages 107–120, 2022. ACM
Aergia: leveraging heterogeneity in federated learning systems [link]Paper   doi   link   bibtex  
AGIC: Approximate Gradient Inversion Attack on Federated Learning. Xu, J.; Hong, C.; Huang, J.; Chen, L. Y.; and Decouchant, J. In 41st International Symposium on Reliable Distributed Systems, SRDS 2022, Vienna, Austria, September 19-22, 2022, pages 12–22, 2022. IEEE
AGIC: Approximate Gradient Inversion Attack on Federated Learning [link]Paper   doi   link   bibtex  
Attacks and Defenses for Free-Riders in Multi-Discriminator GAN. Zhao, Z.; Huang, J.; Roos, S.; and Chen, L. Y. CoRR, abs/2201.09967. 2022.
Attacks and Defenses for Free-Riders in Multi-Discriminator GAN [link]Paper   link   bibtex  
MEGA: Model Stealing via Collaborative Generator-Substitute Networks. Hong, C.; Huang, J.; and Chen, L. Y. CoRR, abs/2202.00008. 2022.
MEGA: Model Stealing via Collaborative Generator-Substitute Networks [link]Paper   link   bibtex  
Blind leads Blind: A Zero-Knowledge Attack on Federated Learning. Huang, J.; Zhao, Z.; Chen, L. Y.; and Roos, S. CoRR, abs/2202.05877. 2022.
Blind leads Blind: A Zero-Knowledge Attack on Federated Learning [link]Paper   link   bibtex  
CTAB-GAN+: Enhancing Tabular Data Synthesis. Zhao, Z.; Kunar, A.; Birke, R.; and Chen, L. Y. CoRR, abs/2204.00401. 2022.
CTAB-GAN+: Enhancing Tabular Data Synthesis [link]Paper   doi   link   bibtex  
Federated Geometric Monte Carlo Clustering to Counter Non-IID Datasets. Lucchetti, F.; Decouchant, J.; Fernandes, M.; Chen, L. Y.; and Völp, M. CoRR, abs/2204.11017. 2022.
Federated Geometric Monte Carlo Clustering to Counter Non-IID Datasets [link]Paper   doi   link   bibtex  
AGIC: Approximate Gradient Inversion Attack on Federated Learning. Xu, J.; Hong, C.; Huang, J.; Chen, L. Y.; and Decouchant, J. CoRR, abs/2204.13784. 2022.
AGIC: Approximate Gradient Inversion Attack on Federated Learning [link]Paper   doi   link   bibtex  
Targeted Influence with Community and Gender-Aware Seeding. Styczen, M.; Chen, B.; Teng, Y.; Pignolet, Y.; Chen, L. Y.; and Yang, D. CoRR, abs/2208.12649. 2022.
Targeted Influence with Community and Gender-Aware Seeding [link]Paper   doi   link   bibtex  
Aergia: Leveraging Heterogeneity in Federated Learning Systems. Cox, B.; Chen, L. Y.; and Decouchant, J. CoRR, abs/2210.06154. 2022.
Aergia: Leveraging Heterogeneity in Federated Learning Systems [link]Paper   doi   link   bibtex  
FCT-GAN: Enhancing Table Synthesis via Fourier Transform. Zhao, Z.; Birke, R.; and Chen, L. Y. CoRR, abs/2210.06239. 2022.
FCT-GAN: Enhancing Table Synthesis via Fourier Transform [link]Paper   doi   link   bibtex  
Federated Learning for Tabular Data: Exploring Potential Risk to Privacy. Wu, H.; Zhao, Z.; Chen, L. Y.; and van Moorsel, A. CoRR, abs/2210.06856. 2022.
Federated Learning for Tabular Data: Exploring Potential Risk to Privacy [link]Paper   doi   link   bibtex  
Permutation-Invariant Tabular Data Synthesis. Zhu, Y.; Zhao, Z.; Birke, R.; and Chen, L. Y. CoRR, abs/2211.09286. 2022.
Permutation-Invariant Tabular Data Synthesis [link]Paper   doi   link   bibtex  
  2021 (30)
Locality Sensitive Hash Aggregated Nonlinear Neighborhood Matrix Factorization for Online Sparse Big Data Analysis. Li, Z.; Li, H.; Li, K.; Wu, F.; Chen, L. Y.; and Li, K. Trans. Data Sci., 2(4): 37:1–37:27. 2021.
Locality Sensitive Hash Aggregated Nonlinear Neighborhood Matrix Factorization for Online Sparse Big Data Analysis [link]Paper   doi   link   bibtex  
Automatic Privacy and Utility Preservation for Mobility Data: A Nonlinear Model-Based Approach. Cerf, S.; Bouchenak, S.; Robu, B.; Marchand, N.; Primault, V.; Mokhtar, S. B.; Boutet, A.; and Chen, L. Y. IEEE Trans. Dependable Secur. Comput., 18(1): 269–282. 2021.
Automatic Privacy and Utility Preservation for Mobility Data: A Nonlinear Model-Based Approach [link]Paper   doi   link   bibtex  
Enhancing Robustness of On-Line Learning Models on Highly Noisy Data. Zhao, Z.; Birke, R.; Han, R.; Robu, B.; Bouchenak, S.; Mokhtar, S. B.; and Chen, L. Y. IEEE Trans. Dependable Secur. Comput., 18(5): 2177–2192. 2021.
Enhancing Robustness of On-Line Learning Models on Highly Noisy Data [link]Paper   doi   link   bibtex  
SlimML: Removing Non-Critical Input Data in Large-Scale Iterative Machine Learning. Han, R.; Liu, C. H.; Li, S.; Chen, L. Y.; Wang, G.; Tang, J.; and Ye, J. IEEE Trans. Knowl. Data Eng., 33(5): 2223–2236. 2021.
SlimML: Removing Non-Critical Input Data in Large-Scale Iterative Machine Learning [link]Paper   doi   link   bibtex  
Guest Editorial: Special Issue on Data Analytics and Machine Learning for Network and Service Management - Part II. Zincir-Heywood, N.; Casale, G.; Carrera, D.; Chen, L. Y.; Dhamdhere, A.; Inoue, T.; Lutfiyya, H.; and Samak, T. IEEE Trans. Netw. Serv. Manag., 18(1): 775–779. 2021.
Guest Editorial: Special Issue on Data Analytics and Machine Learning for Network and Service Management - Part II [link]Paper   doi   link   bibtex  
Accelerating Gossip-Based Deep Learning in Heterogeneous Edge Computing Platforms. Han, R.; Li, S.; Wang, X.; Liu, C. H.; Xin, G.; and Chen, L. Y. IEEE Trans. Parallel Distributed Syst., 32(7): 1591–1602. 2021.
Accelerating Gossip-Based Deep Learning in Heterogeneous Edge Computing Platforms [link]Paper   doi   link   bibtex  
SGD}{\}{_}{_Tucker: A Novel Stochastic Optimization Strategy for Parallel Sparse Tucker Decomposition. Li, H.; Li, Z.; Li, K.; Rellermeyer, J. S.; Chen, L. Y.; and Li, K. IEEE Trans. Parallel Distributed Syst., 32(7): 1828–1841. 2021.
SGD$}{\}{_}{$_Tucker: A Novel Stochastic Optimization Strategy for Parallel Sparse Tucker Decomposition [link]Paper   doi   link   bibtex  
Accurate Differentially Private Deep Learning on the Edge. Han, R.; Li, D.; Ouyang, J.; Liu, C. H.; Wang, G.; Wu, D.; and Chen, L. Y. IEEE Trans. Parallel Distributed Syst., 32(9): 2231–2247. 2021.
Accurate Differentially Private Deep Learning on the Edge [link]Paper   doi   link   bibtex  
sPARE: Partial Replication for Multi-Tier Applications in the Cloud. Birke, R.; Pérez, J. F.; Qiu, Z.; Björkqvist, M.; and Chen, L. Y. IEEE Trans. Serv. Comput., 14(2): 574–588. 2021.
sPARE: Partial Replication for Multi-Tier Applications in the Cloud [link]Paper   doi   link   bibtex  
CTAB-GAN: Effective Table Data Synthesizing. Zhao, Z.; Kunar, A.; Birke, R.; and Chen, L. Y. In Balasubramanian, V. N.; and Tsang, I. W., editor(s), Asian Conference on Machine Learning, ACML 2021, 17-19 November 2021, Virtual Event, volume 157, of Proceedings of Machine Learning Research, pages 97–112, 2021. PMLR
CTAB-GAN: Effective Table Data Synthesizing [link]Paper   link   bibtex  
QActor: Active Learning on Noisy Labels. Younesian, T.; Zhao, Z.; Ghiassi, A.; Birke, R.; and Chen, L. Y. In Balasubramanian, V. N.; and Tsang, I. W., editor(s), Asian Conference on Machine Learning, ACML 2021, 17-19 November 2021, Virtual Event, volume 157, of Proceedings of Machine Learning Research, pages 548–563, 2021. PMLR
QActor: Active Learning on Noisy Labels [link]Paper   link   bibtex  
TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise. Ghiassi, A.; Birke, R.; and Chen, L. Y. In BDCAT '21: 2021 IEEE/ACM 8th International Conference on Big Data Computing, Applications and Technologies, Leicester, United Kingdom, December 6 - 9, 2021, pages 52–62, 2021. ACM
TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise [link]Paper   doi   link   bibtex  
On Influencing the Influential: Disparity Seeding. Teng, Y.; Chen, H.; Yang, D.; Pignolet, Y.; Li, T.; and Chen, L. Y. In Demartini, G.; Zuccon, G.; Culpepper, J. S.; Huang, Z.; and Tong, H., editor(s), CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1 - 5, 2021, pages 1804–1813, 2021. ACM
On Influencing the Influential: Disparity Seeding [link]Paper   doi   link   bibtex  
LABELNET: Recovering Noisy Labels. Ghiassi, A.; Birke, R.; Han, R.; and Chen, L. Y. In International Joint Conference on Neural Networks, IJCNN 2021, Shenzhen, China, July 18-22, 2021, pages 1–8, 2021. IEEE
LABELNET: Recovering Noisy Labels [link]Paper   doi   link   bibtex  
Practical Analysis of Replication-Based Systems. Ciucu, F.; Poloczek, F.; Chen, L. Y.; and Chan, M. In 40th IEEE Conference on Computer Communications, INFOCOM 2021, Vancouver, BC, Canada, May 10-13, 2021, pages 1–10, 2021. IEEE
Practical Analysis of Replication-Based Systems [link]Paper   doi   link   bibtex  
LegoDNN: block-grained scaling of deep neural networks for mobile vision. Han, R.; Zhang, Q.; Liu, C. H.; Wang, G.; Tang, J.; and Chen, L. Y. In ACM MobiCom '21: The 27th Annual International Conference on Mobile Computing and Networking, New Orleans, Louisiana, USA, October 25-29, 2021, pages 406–419, 2021. ACM
LegoDNN: block-grained scaling of deep neural networks for mobile vision [link]Paper   doi   link   bibtex  
Masa: Responsive Multi-DNN Inference on the Edge. Cox, B.; Galjaard, J.; Ghiassi, A.; Birke, R.; and Chen, L. Y. In 19th IEEE International Conference on Pervasive Computing and Communications, PerCom 2021, Kassel, Germany, March 22-26, 2021, pages 1–10, 2021. IEEE
Masa: Responsive Multi-DNN Inference on the Edge [link]Paper   doi   link   bibtex  
MemA: Fast Inference of Multiple Deep Models. Galjaard, J.; Cox, B.; Ghiassi, A.; Chen, L. Y.; and Birke, R. In 19th IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021, Kassel, Germany, March 22-26, 2021, pages 281–286, 2021. IEEE
MemA: Fast Inference of Multiple Deep Models [link]Paper   doi   link   bibtex  
Artifact: Masa: Responsive Multi-DNN Inference on the Edge. Cox, B.; Galjaard, J.; Ghiassi, A.; Birke, R.; and Chen, L. Y. In 19th IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021, Kassel, Germany, March 22-26, 2021, pages 446–447, 2021. IEEE
Artifact: Masa: Responsive Multi-DNN Inference on the Edge [link]Paper   doi   link   bibtex  
Courier: Real-Time Optimal Batch Size Prediction for Latency SLOs in BigDL. Martínez, D. A.; Bobde, S.; Motyka, T.; and Chen, L. Y. In Bourcier, J.; Jiang, Z. M. (.; Bezemer, C.; Cortellessa, V.; Pompeo, D. D.; and Varbanescu, A. L., editor(s), ICPE '21: ACM/SPEC International Conference on Performance Engineering, Virtual Event, France, April 19-21, 2021, pages 133–144, 2021. ACM
Courier: Real-Time Optimal Batch Size Prediction for Latency SLOs in BigDL [link]Paper   doi   link   bibtex  
Online Label Aggregation: A Variational Bayesian Approach. Hong, C.; Ghiassi, A.; Zhou, Y.; Birke, R.; and Chen, L. Y. In Leskovec, J.; Grobelnik, M.; Najork, M.; Tang, J.; and Zia, L., editor(s), WWW '21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021, pages 1904–1915, 2021. ACM / IW3C2
Online Label Aggregation: A Variational Bayesian Approach [link]Paper   doi   link   bibtex  
CTAB-GAN: Effective Table Data Synthesizing. Zhao, Z.; Kunar, A.; der Scheer, H. V.; Birke, R.; and Chen, L. Y. CoRR, abs/2102.08369. 2021.
CTAB-GAN: Effective Table Data Synthesizing [link]Paper   link   bibtex  
Enhancing Robustness of On-line Learning Models on Highly Noisy Data. Zhao, Z.; Birke, R.; Han, R.; Robu, B.; Bouchenak, S.; Mokhtar, S. B.; and Chen, L. Y. CoRR, abs/2103.10824. 2021.
Enhancing Robustness of On-line Learning Models on Highly Noisy Data [link]Paper   link   bibtex  
Is Shapley Value fair? Improving Client Selection for Mavericks in Federated Learning. Huang, J.; Hong, C.; Chen, L. Y.; and Roos, S. CoRR, abs/2106.10734. 2021.
Is Shapley Value fair? Improving Client Selection for Mavericks in Federated Learning [link]Paper   link   bibtex  
DTGAN: Differential Private Training for Tabular GANs. Kunar, A.; Birke, R.; Zhao, Z.; and Chen, L. Y. CoRR, abs/2107.02521. 2021.
DTGAN: Differential Private Training for Tabular GANs [link]Paper   link   bibtex  
Multi-Label Gold Asymmetric Loss Correction with Single-Label Regulators. Pene, C. O.; Ghiassi, A.; Younesian, T.; Birke, R.; and Chen, L. Y. CoRR, abs/2108.02032. 2021.
Multi-Label Gold Asymmetric Loss Correction with Single-Label Regulators [link]Paper   link   bibtex  
Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data. Zhao, Z.; Birke, R.; Kunar, A.; and Chen, L. Y. CoRR, abs/2108.07927. 2021.
Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data [link]Paper   link   bibtex  
ComicGAN: Text-to-Comic Generative Adversarial Network. Proven-Bessel, B.; Zhao, Z.; and Chen, L. Y. CoRR, abs/2109.09120. 2021.
ComicGAN: Text-to-Comic Generative Adversarial Network [link]Paper   link   bibtex  
Locality Sensitive Hash Aggregated Nonlinear Neighbourhood Matrix Factorization for Online Sparse Big Data Analysis. Li, Z.; Li, H.; Li, K.; Wu, F.; Chen, L. Y.; and Li, K. CoRR, abs/2111.11682. 2021.
Locality Sensitive Hash Aggregated Nonlinear Neighbourhood Matrix Factorization for Online Sparse Big Data Analysis [link]Paper   link   bibtex  
LegoDNN: Block-grained Scaling of Deep Neural Networks for Mobile Vision. Han, R.; Zhang, Q.; Liu, C. H.; Wang, G.; Tang, J.; and Chen, L. Y. CoRR, abs/2112.09852. 2021.
LegoDNN: Block-grained Scaling of Deep Neural Networks for Mobile Vision [link]Paper   link   bibtex  
  2020 (16)
A note on advances in scheduling algorithms for Cyber-Physical-Social workflows. Ranjan, R.; Chen, L. Y.; Jayaraman, P. P.; and Zomaya, A. Y. Future Gener. Comput. Syst., 108: 1027–1029. 2020.
A note on advances in scheduling algorithms for Cyber-Physical-Social workflows [link]Paper   doi   link   bibtex  
Guest Editorial: Special Section on Data Analytics and Machine Learning for Network and Service Management-Part I. Zincir-Heywood, N.; Casale, G.; Carrera, D.; Chen, L. Y.; Dhamdhere, A.; Inoue, T.; Lutfiyya, H.; and Samak, T. IEEE Trans. Netw. Serv. Manag., 17(4): 1971–1974. 2020.
Guest Editorial: Special Section on Data Analytics and Machine Learning for Network and Service Management-Part I [link]Paper   doi   link   bibtex  
Holistic Technologies for Managing Internet of Things Services. Ranjan, R.; Hsu, C.; Chen, L. Y.; and Georgakopoulos, D. IEEE Trans. Serv. Comput., 13(4): 597–601. 2020.
Holistic Technologies for Managing Internet of Things Services [link]Paper   doi   link   bibtex  
Making Neighbors Quiet: An Approach to Detect Virtual Resource Contention. Vallone, J.; Birke, R.; and Chen, L. Y. IEEE Trans. Serv. Comput., 13(5): 843–856. 2020.
Making Neighbors Quiet: An Approach to Detect Virtual Resource Contention [link]Paper   doi   link   bibtex  
End-to-End Learning from Noisy Crowd to Supervised Machine Learning Models. Younesian, T.; Hong, C.; Ghiassi, A.; Birke, R.; and Chen, L. Y. In 2nd IEEE International Conference on Cognitive Machine Intelligence, CogMI 2020, Atlanta, GA, USA, October 28-31, 2020, pages 17–26, 2020. IEEE
End-to-End Learning from Noisy Crowd to Supervised Machine Learning Models [link]Paper   doi   link   bibtex  
PipeTune: Pipeline Parallelism of Hyper and System Parameters Tuning for Deep Learning Clusters. Rocha, I.; Morris, N.; Chen, L. Y.; Felber, P.; Birke, R.; and Schiavoni, V. In Silva, D. D.; and Kapitza, R., editor(s), Middleware '20: 21st International Middleware Conference, Delft, The Netherlands, December 7-11, 2020, pages 89–104, 2020. ACM
PipeTune: Pipeline Parallelism of Hyper and System Parameters Tuning for Deep Learning Clusters [link]Paper   doi   link   bibtex  
An Exploratory Analysis on Users' Contributions in Federated Learning. Huang, J.; Talbi, R.; Zhao, Z.; Bouchenak, S.; Chen, L. Y.; and Roos, S. In Second IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications, TPS-ISA 2020, Atlanta, GA, USA, October 28-31, 2020, pages 20–29, 2020. IEEE
An Exploratory Analysis on Users' Contributions in Federated Learning [link]Paper   doi   link   bibtex  
QActor: On-line Active Learning for Noisy Labeled Stream Data. Younesian, T.; Zhao, Z.; Ghiassi, A.; Birke, R.; and Chen, L. Y. CoRR, abs/2001.10399. 2020.
QActor: On-line Active Learning for Noisy Labeled Stream Data [link]Paper   link   bibtex  
ExpertNet: Adversarial Learning and Recovery Against Noisy Labels. Ghiassi, A.; Birke, R.; Han, R.; and Chen, L. Y. CoRR, abs/2007.05305. 2020.
ExpertNet: Adversarial Learning and Recovery Against Noisy Labels [link]Paper   link   bibtex  
TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise. Ghiassi, A.; Younesian, T.; Birke, R.; and Chen, L. Y. CoRR, abs/2007.06324. 2020.
TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise [link]Paper   link   bibtex  
PipeTune: Pipeline Parallelism of Hyper and System Parameters Tuning for Deep Learning Clusters. Rocha, I.; Morris, N.; Chen, L. Y.; Felber, P.; Birke, R.; and Schiavoni, V. CoRR, abs/2010.00501. 2020.
PipeTune: Pipeline Parallelism of Hyper and System Parameters Tuning for Deep Learning Clusters [link]Paper   link   bibtex  
Active Learning for Noisy Data Streams Using Weak and Strong Labelers. Younesian, T.; Epema, D. H. J.; and Chen, L. Y. CoRR, abs/2010.14149. 2020.
Active Learning for Noisy Data Streams Using Weak and Strong Labelers [link]Paper   link   bibtex  
An Exploratory Analysis on Users' Contributions in Federated Learning. Huang, J.; Talbi, R.; Zhao, Z.; Bouchenak, S.; Chen, L. Y.; and Roos, S. CoRR, abs/2011.06830. 2020.
An Exploratory Analysis on Users' Contributions in Federated Learning [link]Paper   link   bibtex  
End-to-End Learning from Noisy Crowd to Supervised Machine Learning Models. Younesian, T.; Hong, C.; Ghiassi, A.; Birke, R.; and Chen, L. Y. CoRR, abs/2011.06833. 2020.
End-to-End Learning from Noisy Crowd to Supervised Machine Learning Models [link]Paper   link   bibtex  
On Influencing the Influential: Disparity Seeding. Teng, A.; Li, T.; Liao, Y.; Chen, H.; Pignolet, Y.; Yang, D.; and Chen, L. Y. CoRR, abs/2011.08946. 2020.
On Influencing the Influential: Disparity Seeding [link]Paper   link   bibtex  
SGD_Tucker: A Novel Stochastic Optimization Strategy for Parallel Sparse Tucker Decomposition. Li, H.; Li, Z.; Li, K.; Rellermeyer, J. S.; Chen, L. Y.; and Li, K. CoRR, abs/2012.03550. 2020.
SGD_Tucker: A Novel Stochastic Optimization Strategy for Parallel Sparse Tucker Decomposition [link]Paper   link   bibtex  
  2019 (9)
Workload-Adaptive Configuration Tuning for Hierarchical Cloud Schedulers. Han, R.; Liu, C. H.; Zong, Z.; Chen, L. Y.; Liu, W.; Wang, S.; and Zhan, J. IEEE Trans. Parallel Distributed Syst., 30(12): 2879–2895. 2019.
Workload-Adaptive Configuration Tuning for Hierarchical Cloud Schedulers [link]Paper   doi   link   bibtex  
Automating Deep Neural Network Model Selection for Edge Inference. Lu, B.; Yang, J.; Chen, L. Y.; and Ren, S. In 2019 IEEE First International Conference on Cognitive Machine Intelligence (CogMI), Los Angeles, CA, USA, December 12-14, 2019, pages 184–193, 2019. IEEE
Automating Deep Neural Network Model Selection for Edge Inference [link]Paper   doi   link   bibtex  
Robust Anomaly Detection on Unreliable Data. Zhao, Z.; Cerf, S.; Birke, R.; Robu, B.; Bouchenak, S.; Mokhtar, S. B.; and Chen, L. Y. In 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2019, Portland, OR, USA, June 24-27, 2019, pages 630–637, 2019. IEEE
Robust Anomaly Detection on Unreliable Data [link]Paper   doi   link   bibtex  
Chisel: Reshaping Queries to Trim Latency in Key-Value Stores. Birke, R.; Pérez, J. F.; Mokhtar, S. B.; Rameshan, N.; and Chen, L. Y. In 2019 IEEE International Conference on Autonomic Computing, ICAC 2019, Umeå, Sweden, June 16-20, 2019, pages 42–51, 2019. IEEE
Chisel: Reshaping Queries to Trim Latency in Key-Value Stores [link]Paper   doi   link   bibtex  
Differential Approximation and Sprinting for Multi-Priority Big Data Engines. Birke, R.; Rocha, I.; Pérez, J. F.; Schiavoni, V.; Felber, P.; and Chen, L. Y. In Proceedings of the 20th International Middleware Conference, Middleware 2019, Davis, CA, USA, December 9-13, 2019, pages 202–214, 2019. ACM
Differential Approximation and Sprinting for Multi-Priority Big Data Engines [link]Paper   doi   link   bibtex  
Robust (Deep) Learning Framework Against Dirty Labels and Beyond. Ghiassi, A.; Younesian, T.; Zhao, Z.; Birke, R.; Schiavoni, V.; and Chen, L. Y. In First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications, TPS-ISA 2019, Los Angeles, CA, USA, December 12-14, 2019, pages 236–244, 2019. IEEE
Robust (Deep) Learning Framework Against Dirty Labels and Beyond [link]Paper   doi   link   bibtex  
Opportunities and Challenges for Resource Management and Machine Learning Clusters. Chen, L. Y. In Johnson, K.; Spillner, J.; Klusácek, D.; and Anjum, A., editor(s), Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2019, Companion Volume, Auckland, New Zealand, December 2-5, 2019, pages 165–166, 2019. ACM
Opportunities and Challenges for Resource Management and Machine Learning Clusters [link]Paper   doi   link   bibtex  
Differential Approximation and Sprinting for Multi-Priority Big Data Engines. Birke, R.; Rocha, I.; Pérez, J. F.; Schiavoni, V.; Felber, P.; and Chen, L. Y. CoRR, abs/1909.05531. 2019.
Differential Approximation and Sprinting for Multi-Priority Big Data Engines [link]Paper   link   bibtex  
RAD: On-line Anomaly Detection for Highly Unreliable Data. Zhao, Z.; Birke, R.; Han, R.; Robu, B.; Bouchenak, S.; Mokhtar, S. B.; and Chen, L. Y. CoRR, abs/1911.04383. 2019.
RAD: On-line Anomaly Detection for Highly Unreliable Data [link]Paper   link   bibtex  
  2018 (11)
Holistic Workload Scaling: A New Approach to Compute Acceleration in the Cloud. Pérez, J. F.; Chen, L. Y.; Villari, M.; and Ranjan, R. IEEE Cloud Comput., 5(1): 20–30. 2018.
Holistic Workload Scaling: A New Approach to Compute Acceleration in the Cloud [link]Paper   doi   link   bibtex  
A multi-layered performance analysis for cloud-based topic detection and tracking in Big Data applications. Wang, M.; Jayaraman, P. P.; Solaiman, E.; Chen, L. Y.; Li, Z.; Song, J.; Georgakopoulos, D.; and Ranjan, R. Future Gener. Comput. Syst., 87: 580–590. 2018.
A multi-layered performance analysis for cloud-based topic detection and tracking in Big Data applications [link]Paper   doi   link   bibtex  
Effective Capacity Modulation as an Explicit Control Knob for Public Cloud Profitability. Wang, C.; Urgaonkar, B.; Kesidis, G.; Gupta, A.; Chen, L. Y.; and Birke, R. ACM Trans. Auton. Adapt. Syst., 13(1): 2:1–2:25. 2018.
Effective Capacity Modulation as an Explicit Control Knob for Public Cloud Profitability [link]Paper   doi   link   bibtex  
Optimizing for Tail Sojourn Times of Cloud Clusters. Björkqvist, M.; Gautam, N.; Birke, R.; Chen, L. Y.; and Binder, W. IEEE Trans. Cloud Comput., 6(1): 156–167. 2018.
Optimizing for Tail Sojourn Times of Cloud Clusters [link]Paper   doi   link   bibtex  
Spatial-Temporal Prediction Models for Active Ticket Managing in Data Centers. Xue, J.; Birke, R.; Chen, L. Y.; and Smirni, E. IEEE Trans. Netw. Serv. Manag., 15(1): 39–52. 2018.
Spatial-Temporal Prediction Models for Active Ticket Managing in Data Centers [link]Paper   doi   link   bibtex  
Towards Dynamic End-to-End Privacy Preserving Data Classification. Talbi, R.; Bouchenak, S.; and Chen, L. Y. In 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, DSN Workshops 2018, Luxembourg, June 25-28, 2018, pages 73–74, 2018. IEEE Computer Society
Towards Dynamic End-to-End Privacy Preserving Data Classification [link]Paper   doi   link   bibtex  
Model-driven computational sprinting. Morris, N.; Stewart, C.; Chen, L. Y.; Birke, R.; and Kelley, J. In Oliveira, R.; Felber, P.; and Hu, Y. C., editor(s), Proceedings of the Thirteenth EuroSys Conference, EuroSys 2018, Porto, Portugal, April 23-26, 2018, pages 38:1–38:13, 2018. ACM
Model-driven computational sprinting [link]Paper   doi   link   bibtex  
SmallTail: Scaling Cores and Probabilistic Cloning Requests for Web Systems. Lakew, E. B.; Birke, R.; Pérez, J. F.; Elmroth, E.; and Chen, L. Y. In 2018 IEEE International Conference on Autonomic Computing, ICAC 2018, Trento, Italy, September 3-7, 2018, pages 31–40, 2018. IEEE Computer Society
SmallTail: Scaling Cores and Probabilistic Cloning Requests for Web Systems [link]Paper   doi   link   bibtex  
AdaptiveConfig: Run-Time Configuration of Cluster Schedulers for Cloud Short-Running Jobs. Han, R.; Zong, Z.; Chen, L. Y.; Wang, S.; and Zhan, J. In 38th IEEE International Conference on Distributed Computing Systems, ICDCS 2018, Vienna, Austria, July 2-6, 2018, pages 1519–1526, 2018. IEEE Computer Society
AdaptiveConfig: Run-Time Configuration of Cluster Schedulers for Cloud Short-Running Jobs [link]Paper   doi   link   bibtex  
A Speech and Lip Authentication System Based On Android Smart Phone. Zhang, X.; Zhang, J.; He, T.; Chen, L. Y.; Shen, Y.; and Xu, X. In Proceedings of the 6th International Conference on Information Technology: IoT and Smart City, December 29-31, Hong Kong, China, pages 110–114, 2018. ACM
A Speech and Lip Authentication System Based On Android Smart Phone [link]Paper   doi   link   bibtex  
Héron: Taming Tail Latencies in Key-Value Stores Under Heterogeneous Workloads. Jaiman, V.; Mokhtar, S. B.; Quéma, V.; Chen, L. Y.; and Rivière, E. In 37th IEEE Symposium on Reliable Distributed Systems, SRDS 2018, Salvador, Brazil, October 2-5, 2018, pages 191–200, 2018. IEEE Computer Society
Héron: Taming Tail Latencies in Key-Value Stores Under Heterogeneous Workloads [link]Paper   doi   link   bibtex  
  2017 (17)
Software Defined Membrane: Policy-Driven Edge and Internet of Things Security. Villari, M.; Fazio, M.; Dustdar, S.; Rana, O. F.; Chen, L. Y.; and Ranjan, R. IEEE Cloud Comput., 4(4): 92–99. 2017.
Software Defined Membrane: Policy-Driven Edge and Internet of Things Security [link]Paper   doi   link   bibtex  
Bringing 5G into Rural and Low-Income Areas: Is It Feasible?. Chiaraviglio, L.; Blefari-Melazzi, N.; Liu, W.; Gutiérrez, J. A.; van de Beek, J.; Birke, R.; Chen, L. Y.; Idzikowski, F.; Kilper, D. C.; Monti, P.; Bagula, A. B.; and Wu, J. IEEE Commun. Stand. Mag., 1(3): 50–57. 2017.
Bringing 5G into Rural and Low-Income Areas: Is It Feasible? [link]Paper   doi   link   bibtex  
Reprint of "Robust partial-load experiments with Showstopper". Podzimek, A.; Bulej, L.; Chen, L. Y.; Binder, W.; and Tuma, P. Future Gener. Comput. Syst., 72: 81–104. 2017.
Reprint of "Robust partial-load experiments with Showstopper" [link]Paper   doi   link   bibtex  
Priority Scheduling for Heterogeneous Workloads: Tradeoff Between Evictions and Response Time. Cavdar, D.; Chen, L. Y.; and Alagöz, F. IEEE Syst. J., 11(2): 684–695. 2017.
Priority Scheduling for Heterogeneous Workloads: Tradeoff Between Evictions and Response Time [link]Paper   doi   link   bibtex  
Cutting Latency Tail: Analyzing and Validating Replication without Canceling. Qiu, Z.; Pérez, J. F.; Birke, R.; Chen, L. Y.; and Harrison, P. G. IEEE Trans. Parallel Distributed Syst., 28(11): 3128–3141. 2017.
Cutting Latency Tail: Analyzing and Validating Replication without Canceling [link]Paper   doi   link   bibtex  
Failure Analysis and Prediction for Big-Data Systems. Rosà, A.; Chen, L. Y.; and Binder, W. IEEE Trans. Serv. Comput., 10(6): 984–998. 2017.
Failure Analysis and Prediction for Big-Data Systems [link]Paper   doi   link   bibtex  
Early work on modeling computational sprinting. Morris, N.; Stewart, C.; Birke, R.; Chen, L. Y.; and Kelley, J. In Proceedings of the 2017 Symposium on Cloud Computing, SoCC 2017, Santa Clara, CA, USA, September 24-27, 2017, pages 661, 2017. ACM
Early work on modeling computational sprinting [link]Paper   doi   link   bibtex  
Meeting Latency Target in Transient Burst: A Case on Spark Streaming. Birke, R.; Björkqvist, M.; Kalyvianaki, E.; and Chen, L. Y. In 2017 IEEE International Conference on Cloud Engineering, IC2E 2017, Vancouver, BC, Canada, April 4-7, 2017, pages 149–158, 2017. IEEE Computer Society
Meeting Latency Target in Transient Burst: A Case on Spark Streaming [link]Paper   doi   link   bibtex  
AccStream: Accuracy-Aware Overload Management for Stream Processing Systems. Sun, H.; Birke, R.; Binder, W.; Björkqvist, M.; and Chen, L. Y. In Wang, X.; Stewart, C.; and Lei, H., editor(s), 2017 IEEE International Conference on Autonomic Computing, ICAC 2017, Columbus, OH, USA, July 17-21, 2017, pages 39–48, 2017. IEEE Computer Society
AccStream: Accuracy-Aware Overload Management for Stream Processing Systems [link]Paper   doi   link   bibtex  
Dual Scaling VMs and Queries: Cost-Effective Latency Curtailment. Pérez, J. F.; Birke, R.; Björkqvist, M.; and Chen, L. Y. In Lee, K.; and Liu, L., editor(s), 37th IEEE International Conference on Distributed Computing Systems, ICDCS 2017, Atlanta, GA, USA, June 5-8, 2017, pages 988–998, 2017. IEEE Computer Society
Dual Scaling VMs and Queries: Cost-Effective Latency Curtailment [link]Paper   doi   link   bibtex  
Power of redundancy: Designing partial replication for multi-tier applications. Birke, R.; Pérez, J. F.; Qiu, Z.; Björkqvist, M.; and Chen, L. Y. In 2017 IEEE Conference on Computer Communications, INFOCOM 2017, Atlanta, GA, USA, May 1-4, 2017, pages 1–9, 2017. IEEE
Power of redundancy: Designing partial replication for multi-tier applications [link]Paper   doi   link   bibtex  
On the latency-accuracy tradeoff in approximate MapReduce jobs. Pérez, J. F.; Birke, R.; and Chen, L. Y. In 2017 IEEE Conference on Computer Communications, INFOCOM 2017, Atlanta, GA, USA, May 1-4, 2017, pages 1–9, 2017. IEEE
On the latency-accuracy tradeoff in approximate MapReduce jobs [link]Paper   doi   link   bibtex  
Work-in-Progress: Maximizing Model Accuracy in Real-time and Iterative Machine Learning. Han, R.; Zhang, F.; Chen, L. Y.; and Zhan, J. In 2017 IEEE Real-Time Systems Symposium, RTSS 2017, Paris, France, December 5-8, 2017, pages 351–353, 2017. IEEE Computer Society
Work-in-Progress: Maximizing Model Accuracy in Real-time and Iterative Machine Learning [link]Paper   doi   link   bibtex  
PULP: Achieving Privacy and Utility Trade-Off in User Mobility Data. Cerf, S.; Primault, V.; Boutet, A.; Mokhtar, S. B.; Birke, R.; Bouchenak, S.; Chen, L. Y.; Marchand, N.; and Robu, B. In 36th IEEE Symposium on Reliable Distributed Systems, SRDS 2017, Hong Kong, Hong Kong, September 26-29, 2017, pages 164–173, 2017. IEEE Computer Society
PULP: Achieving Privacy and Utility Trade-Off in User Mobility Data [link]Paper   doi   link   bibtex  
State of Practice of Non-self-aware Virtual Machine Management in Cloud Data Centers. Chen, L. Y.; Birke, R.; and Smirni, E. In Kounev, S.; Kephart, J. O.; Milenkoski, A.; and Zhu, X., editor(s), Self-Aware Computing Systems, pages 555–574. Springer International Publishing, 2017.
State of Practice of Non-self-aware Virtual Machine Management in Cloud Data Centers [link]Paper   doi   link   bibtex  
Self-aware Computing Systems: Open Challenges and Future Research Directions. Birke, R.; Cámara, J.; Chen, L. Y.; Esterle, L.; Geihs, K.; Gelenbe, E.; Giese, H.; Robertsson, A.; and Zhu, X. In Kounev, S.; Kephart, J. O.; Milenkoski, A.; and Zhu, X., editor(s), Self-Aware Computing Systems, pages 709–722. Springer International Publishing, 2017.
Self-aware Computing Systems: Open Challenges and Future Research Directions [link]Paper   doi   link   bibtex  
Distributed Applications and Interoperable Systems - 17th IFIP WG 6.1 International Conference, DAIS 2017, Held as Part of the 12th International Federated Conference on Distributed Computing Techniques, DisCoTec 2017, Neuchâtel, Switzerland, June 19-22, 2017, Proceedings. Chen, L. Y.; and Reiser, H. P., editors. Volume 10320, of Lecture Notes in Computer Science.Springer. 2017.
Distributed Applications and Interoperable Systems - 17th IFIP WG 6.1 International Conference, DAIS 2017, Held as Part of the 12th International Federated Conference on Distributed Computing Techniques, DisCoTec 2017, Neuchâtel, Switzerland, June 19-22, 2017, Proceedings [link]Paper   doi   link   bibtex  
  2016 (23)
Open Issues in Scheduling Microservices in the Cloud. Fazio, M.; Celesti, A.; Ranjan, R.; Liu, C.; Chen, L. Y.; and Villari, M. IEEE Cloud Comput., 3(5): 81–88. 2016.
Open Issues in Scheduling Microservices in the Cloud [link]Paper   doi   link   bibtex  
Robust partial-load experiments with Showstopper. Podzimek, A.; Bulej, L.; Chen, L. Y.; Binder, W.; and Tuma, P. Future Gener. Comput. Syst., 64: 15–38. 2016.
Robust partial-load experiments with Showstopper [link]Paper   doi   link   bibtex  
Virtualization in the Private Cloud: State of the Practice. Birke, R.; Podzimek, A.; Chen, L. Y.; and Smirni, E. IEEE Trans. Netw. Serv. Manag., 13(3): 608–621. 2016.
Virtualization in the Private Cloud: State of the Practice [link]Paper   doi   link   bibtex  
On Fair Attribution of Costs Under Peak-Based Pricing to Cloud Tenants. Nasiriani, N.; Wang, C.; Kesidis, G.; Urgaonkar, B.; Chen, L. Y.; and Birke, R. ACM Trans. Model. Perform. Evaluation Comput. Syst., 2(1): 3:1–3:28. 2016.
On Fair Attribution of Costs Under Peak-Based Pricing to Cloud Tenants [link]Paper   doi   link   bibtex  
Discharging the Network From Its Flow Control Headaches: Packet Drops and HOL Blocking. Chrysos, N.; Chen, L. Y.; Kachris, C.; and Katevenis, M. IEEE/ACM Trans. Netw., 24(1): 15–28. 2016.
Discharging the Network From Its Flow Control Headaches: Packet Drops and HOL Blocking [link]Paper   doi   link   bibtex  
AkkaProf: A Profiler for Akka Actors in Parallel and Distributed Applications. Rosà, A.; Chen, L. Y.; and Binder, W. In Igarashi, A., editor(s), Programming Languages and Systems - 14th Asian Symposium, APLAS 2016, Hanoi, Vietnam, November 21-23, 2016, Proceedings, volume 10017, of Lecture Notes in Computer Science, pages 139–147, 2016.
AkkaProf: A Profiler for Akka Actors in Parallel and Distributed Applications [link]Paper   doi   link   bibtex  
Integrated Energy Efficient Data Centre Management for Green Cloud Computing - The FP7 GENiC Project Experience. Torrens, J. I.; Mehta, D.; Zavrel, V.; Grimes, D.; Scherer, T.; Birke, R.; Chen, L. Y.; Rea, S.; Lopez, L.; Pages, E.; and Pesch, D. In Cardoso, J.; Ferguson, D.; Muñoz, V. M.; and Helfert, M., editor(s), CLOSER 2016 - Proceedings of the 6th International Conference on Cloud Computing and Services Science, Volume 2, Rome, Italy, April 23-25, 2016, pages 375–386, 2016. SciTePress
Integrated Energy Efficient Data Centre Management for Green Cloud Computing - The FP7 GENiC Project Experience [link]Paper   doi   link   bibtex  
Profiling Memory Vulnerability of Big-Data Applications. Rameshan, N.; Birke, R.; Navarro, L.; Vlassov, V.; Urgaonkar, B.; Kesidis, G.; Schmatz, M. L.; and Chen, L. Y. In 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, DSN Workshops 2016, Toulouse, France, June 28 - July 1, 2016, pages 258–261, 2016. IEEE Computer Society
Profiling Memory Vulnerability of Big-Data Applications [link]Paper   doi   link   bibtex  
Managing Data Center Tickets: Prediction and Active Sizing. Xue, J.; Birke, R.; Chen, L. Y.; and Smirni, E. In 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2016, Toulouse, France, June 28 - July 1, 2016, pages 335–346, 2016. IEEE Computer Society
Managing Data Center Tickets: Prediction and Active Sizing [link]Paper   doi   link   bibtex  
Efficient profiling of actor-based applications in parallel and distributed systems. Rosà, A.; Chen, L. Y.; and Binder, W. In Proceedings of the 11th Workshop on Implementation, Compilation, Optimization of Object-Oriented Languages, Programs and Systems, ICOOOLPS@ECOOP 2016, Rome, Italy, July 17-22, 2016, pages 9:1–9:3, 2016. ACM
Efficient profiling of actor-based applications in parallel and distributed systems [link]Paper   doi   link   bibtex  
Profiling actor utilization and communication in Akka. Rosà, A.; Chen, L. Y.; and Binder, W. In Tóth, M.; and Fritchie, S. L., editor(s), Proceedings of the 15th International Workshop on Erlang, Nara, Japan, September 18-22, 2016, pages 24–32, 2016. ACM
Profiling actor utilization and communication in Akka [link]Paper   doi   link   bibtex  
Actor profiling in virtual execution environments. Rosà, A.; Chen, L. Y.; and Binder, W. In Fischer, B.; and Schaefer, I., editor(s), Proceedings of the 2016 ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences, GPCE 2016, Amsterdam, The Netherlands, October 31 - November 1, 2016, pages 36–46, 2016. ACM
Actor profiling in virtual execution environments [link]Paper   doi   link   bibtex  
Dynamic Block Sizing for Data Stream Processing Systems. Birke, R.; Kalyvianaki, E.; Binder, W.; Schmatz, M. L.; and Chen, L. Y. In 2016 IEEE International Conference on Cloud Engineering Workshop, IC2E Workshops, Berlin, Germany, April 4-8, 2016, pages 216–222, 2016. IEEE Computer Society
Dynamic Block Sizing for Data Stream Processing Systems [link]Paper   doi   link   bibtex  
Effective Capacity Modulation as an Explicit Control Knob for Public Cloud Profitability. Wang, C.; Urgaonkar, B.; Gupta, A.; Chen, L. Y.; Birke, R.; and Kesidis, G. In Kounev, S.; Giese, H.; and Liu, J., editor(s), 2016 IEEE International Conference on Autonomic Computing, ICAC 2016, Wuerzburg, Germany, July 17-22, 2016, pages 95–104, 2016. IEEE Computer Society
Effective Capacity Modulation as an Explicit Control Knob for Public Cloud Profitability [link]Paper   doi   link   bibtex  
Sprint Ability: How Well Does Your Software Exploit Bursts in Processing Capacity?. Morris, N.; Renganathan, S. M.; Stewart, C.; Birke, R.; and Chen, L. Y. In Kounev, S.; Giese, H.; and Liu, J., editor(s), 2016 IEEE International Conference on Autonomic Computing, ICAC 2016, Wuerzburg, Germany, July 17-22, 2016, pages 173–178, 2016. IEEE Computer Society
Sprint Ability: How Well Does Your Software Exploit Bursts in Processing Capacity? [link]Paper   doi   link   bibtex  
Dslash: Managing Data in Overloaded Batch Streaming Systems. Birke, R.; Björkqvist, M.; Kalyvianaki, E.; and Chen, L. Y. In 36th IEEE International Conference on Distributed Computing Systems, ICDCS 2016, Nara, Japan, June 27-30, 2016, pages 745–746, 2016. IEEE Computer Society
Dslash: Managing Data in Overloaded Batch Streaming Systems [link]Paper   doi   link   bibtex  
An Endpoint Communication Profiling Tool for Distributed Computing Frameworks. Rosà, A.; Chen, L. Y.; and Binder, W. In 36th IEEE International Conference on Distributed Computing Systems, ICDCS 2016, Nara, Japan, June 27-30, 2016, pages 765–766, 2016. IEEE Computer Society
An Endpoint Communication Profiling Tool for Distributed Computing Frameworks [link]Paper   doi   link   bibtex  
Defeating variability in cloud applications by multi-tier workload redundancy. Birke, R.; Qiu, Z.; Pérez, J. F.; and Chen, L. Y. In IEEE Conference on Computer Communications Workshops, INFOCOM Workshops 2016, San Francisco, CA, USA, April 10-14, 2016, pages 496–497, 2016. IEEE
Defeating variability in cloud applications by multi-tier workload redundancy [link]Paper   doi   link   bibtex  
5G in rural and low-income areas: Are we ready?. Chiaraviglio, L.; Blefari-Melazzi, N.; Liu, W.; Gutiérrez, J. A.; van de Beek, J.; Birke, R.; Chen, L. Y.; Idzikowski, F.; Kilper, D. C.; Monti, P.; and Wu, J. In 2016 ITU Kaleidoscope: ICTs for a Sustainable World, Bangkok, Thailand, November 14-16, 2016, pages 1–8, 2016. IEEE
5G in rural and low-income areas: Are we ready? [link]Paper   doi   link   bibtex  
Robust Server Consolidation: Coping with Peak Demand Underestimation. Grimes, D.; Mehta, D.; O'Sullivan, B.; Birke, R.; Chen, L. Y.; Scherer, T.; and Castiñeiras, I. In 24th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2016, London, United Kingdom, September 19-21, 2016, pages 271–276, 2016. IEEE Computer Society
Robust Server Consolidation: Coping with Peak Demand Underestimation [link]Paper   doi   link   bibtex  
Tale of Tails: Anomaly Avoidance in Data Centers. Xue, J.; Birke, R.; Chen, L. Y.; and Smirni, E. In 35th IEEE Symposium on Reliable Distributed Systems, SRDS 2016, Budapest, Hungary, September 26-29, 2016, pages 91–100, 2016. IEEE Computer Society
Tale of Tails: Anomaly Avoidance in Data Centers [link]Paper   doi   link   bibtex  
AutoBench: Finding Workloads That You Need Using Pluggable Hybrid Analyses. Zheng, Y.; Rosà, A.; Salucci, L.; Li, Y.; Sun, H.; Javed, O.; Bulej, L.; Chen, L. Y.; Qi, Z.; and Binder, W. In IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering, SANER 2016, Suita, Osaka, Japan, March 14-18, 2016 - Volume 1, pages 639–643, 2016. IEEE Computer Society
AutoBench: Finding Workloads That You Need Using Pluggable Hybrid Analyses [link]Paper   doi   link   bibtex  
PROST: Predicting Resource Usages with Spatial and Temporal Dependencies. Xue, J.; Smirni, E.; Scherer, T.; Birke, R.; and Chen, L. Y. In Avritzer, A.; Iosup, A.; Zhu, X.; and Becker, S., editor(s), Proceedings of the 7th ACM/SPEC International Conference on Performance Engineering, ICPE 2016, Delft, The Netherlands, March 12-16, 2016, pages 125–126, 2016. ACM
PROST: Predicting Resource Usages with Spatial and Temporal Dependencies [link]Paper   doi   link   bibtex  
  2015 (19)
A simulation framework for priority scheduling on heterogeneous clusters. Çavdar, D.; Birke, R.; Chen, L. Y.; and Alagöz, F. Future Gener. Comput. Syst., 52: 37–48. 2015.
A simulation framework for priority scheduling on heterogeneous clusters [link]Paper   doi   link   bibtex  
Demystifying Casualties of Evictions in Big Data Priority Scheduling. Rosà, A.; Chen, L. Y.; Birke, R.; and Binder, W. SIGMETRICS Perform. Evaluation Rev., 42(4): 12–21. 2015.
Demystifying Casualties of Evictions in Big Data Priority Scheduling [link]Paper   doi   link   bibtex  
On Energyaware Allocation and Execution for Batch and Interactive MapReduce. Ying, Y.; Birke, R.; Wang, C.; Chen, L. Y.; and Gautam, N. SIGMETRICS Perform. Evaluation Rev., 42(4): 22–30. 2015.
On Energyaware Allocation and Execution for Batch and Interactive MapReduce [link]Paper   doi   link   bibtex  
Analyzing the Impact of CPU Pinning and Partial CPU Loads on Performance and Energy Efficiency. Podzimek, A.; Bulej, L.; Chen, L. Y.; Binder, W.; and Tuma, P. In 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2015, Shenzhen, China, May 4-7, 2015, pages 1–10, 2015. IEEE Computer Society
Analyzing the Impact of CPU Pinning and Partial CPU Loads on Performance and Energy Efficiency [link]Paper   doi   link   bibtex  
Predicting and Mitigating Jobs Failures in Big Data Clusters. Rosà, A.; Chen, L. Y.; and Binder, W. In 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2015, Shenzhen, China, May 4-7, 2015, pages 221–230, 2015. IEEE Computer Society
Predicting and Mitigating Jobs Failures in Big Data Clusters [link]Paper   doi   link   bibtex  
Understanding Unsuccessful Executions in Big-Data Systems. Rosà, A.; Chen, L. Y.; and Binder, W. In 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2015, Shenzhen, China, May 4-7, 2015, pages 741–744, 2015. IEEE Computer Society
Understanding Unsuccessful Executions in Big-Data Systems [link]Paper   doi   link   bibtex  
PRACTISE: Robust prediction of data center time series. Xue, J.; Yan, F.; Birke, R.; Chen, L. Y.; Scherer, T.; and Smirni, E. In Tortonesi, M.; Schönwälder, J.; Madeira, E. R. M.; Schmitt, C.; and Serrat, J., editor(s), 11th International Conference on Network and Service Management, CNSM 2015, Barcelona, Spain, November 9-13, 2015, pages 126–134, 2015. IEEE Computer Society
PRACTISE: Robust prediction of data center time series [link]Paper   doi   link   bibtex  
Understanding the Dark Side of Big Data Clusters: An Analysis beyond Failures. Rosà, A.; Chen, L. Y.; and Binder, W. In 45th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2015, Rio de Janeiro, Brazil, June 22-25, 2015, pages 207–218, 2015. IEEE Computer Society
Understanding the Dark Side of Big Data Clusters: An Analysis beyond Failures [link]Paper   doi   link   bibtex  
Recouping Energy Costs From Cloud Tenants: Tenant Demand Response Aware Pricing Design. Wang, C.; Nasiriani, N.; Kesidis, G.; Urgaonkar, B.; Wang, Q.; Chen, L. Y.; Gupta, A.; and Birke, R. In Kalyanaraman, S.; Seetharam, D. P.; Shorey, R.; Ramchurn, S. D.; and Srivastava, M., editor(s), Proceedings of the 2015 ACM Sixth International Conference on Future Energy Systems, e-Energy 2015, Bangalore, India, July 14-17, 2015, pages 141–150, 2015. ACM
Recouping Energy Costs From Cloud Tenants: Tenant Demand Response Aware Pricing Design [link]Paper   doi   link   bibtex  
Optimizing Energy, Locality and Priority in a MapReduce Cluster. Ying, Y.; Birke, R.; Wang, C.; Chen, L. Y.; and Gautam, N. In 2015 IEEE International Conference on Autonomic Computing, Grenoble, France, July 7-10, 2015, pages 21–30, 2015. IEEE Computer Society
Optimizing Energy, Locality and Priority in a MapReduce Cluster [link]Paper   doi   link   bibtex  
Optimizing capacity allocation for big data applications in cloud datacenters. Spicuglia, S.; Chen, L. Y.; Birke, R.; and Binder, W. In Badonnel, R.; Xiao, J.; Ata, S.; Turck, F. D.; Groza, V.; and dos Santos, C. R. P., editor(s), IFIP/IEEE International Symposium on Integrated Network Management, IM 2015, Ottawa, ON, Canada, 11-15 May, 2015, pages 511–517, 2015. IEEE
Optimizing capacity allocation for big data applications in cloud datacenters [link]Paper   doi   link   bibtex  
Catching the response time tail in the cloud. Spicuglia, S.; Björkqvist, M.; Chen, L. Y.; and Binder, W. In Badonnel, R.; Xiao, J.; Ata, S.; Turck, F. D.; Groza, V.; and dos Santos, C. R. P., editor(s), IFIP/IEEE International Symposium on Integrated Network Management, IM 2015, Ottawa, ON, Canada, 11-15 May, 2015, pages 572–577, 2015. IEEE
Catching the response time tail in the cloud [link]Paper   doi   link   bibtex  
Catching failures of failures at big-data clusters: A two-level neural network approach. Rosà, A.; Chen, L. Y.; and Binder, W. In 23rd IEEE International Symposium on Quality of Service, IWQoS 2015, Portland, OR, USA, June 15-16, 2015, pages 231–236, 2015. IEEE
Catching failures of failures at big-data clusters: A two-level neural network approach [link]Paper   doi   link   bibtex  
Contention detection by throttling: A black-box on-line approach. Vallone, J.; Birke, R.; Chen, L. Y.; and Falsafi, B. In 23rd IEEE International Symposium on Quality of Service, IWQoS 2015, Portland, OR, USA, June 15-16, 2015, pages 237–242, 2015. IEEE
Contention detection by throttling: A black-box on-line approach [link]Paper   doi   link   bibtex  
On Fair Attribution of Costs under Peak-Based Pricing to Cloud Tenants. Nasiriani, N.; Wang, C.; Kesidis, G.; Urgaonkar, B.; Chen, L. Y.; and Birke, R. In 23rd IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2015, Atlanta, GA, USA, October 5-7, 2015, pages 51–60, 2015. IEEE Computer Society
On Fair Attribution of Costs under Peak-Based Pricing to Cloud Tenants [link]Paper   doi   link   bibtex  
When Virtual Meets Physical at the Edge: A Field Study on Datacenters' Virtual Traffic. Birke, R.; Björkqvist, M.; Minkenberg, C.; Schmatz, M. L.; and Chen, L. Y. In Lin, B.; Xu, J. (.; Sengupta, S.; and Shah, D., editor(s), Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, Portland, OR, USA, June 15-19, 2015, pages 403–415, 2015. ACM
When Virtual Meets Physical at the Edge: A Field Study on Datacenters' Virtual Traffic [link]Paper   doi   link   bibtex  
PRACTISE - Demonstrating a Neural Network Based Framework for Robust Prediction of Data Center Workload. Scherer, T.; Xue, J.; Yan, F.; Birke, R.; Chen, L. Y.; and Smirni, E. In Raicu, I.; Rana, O. F.; and Buyya, R., editor(s), 8th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2015, Limassol, Cyprus, December 7-10, 2015, pages 402–403, 2015. IEEE Computer Society
PRACTISE - Demonstrating a Neural Network Based Framework for Robust Prediction of Data Center Workload [link]Paper   doi   link   bibtex  
The GENiC Architecture for Integrated Data Centre Energy Management. Pesch, D.; McGibney, A.; Sobonski, P.; Rea, S.; Scherer, T.; Chen, L. Y.; Engbersen, T.; Mehta, D.; O'Sullivan, B.; Pages, E.; Townley, J.; Kasinathan, D.; Torrens, J. I.; Zavrel, V.; and Hensen, J. L. M. In Raicu, I.; Rana, O. F.; and Buyya, R., editor(s), 8th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2015, Limassol, Cyprus, December 7-10, 2015, pages 540–546, 2015. IEEE Computer Society
The GENiC Architecture for Integrated Data Centre Energy Management [link]Paper   doi   link   bibtex  
Usage Patterns in Multi-tenant Data Centers: a Large-Case Field Study. Birke, R.; Chen, L. Y.; and Smirni, E. In Khan, S. U.; and Zomaya, A. Y., editor(s), Handbook on Data Centers, pages 1257–1266. Springer, 2015.
Usage Patterns in Multi-tenant Data Centers: a Large-Case Field Study [link]Paper   doi   link   bibtex  
  2014 (8)
What to expect when you are consolidating: effective prediction models of application performance on multicores. Chen, L. Y.; Serazzi, G.; Ansaloni, D.; Smirni, E.; and Binder, W. Clust. Comput., 17(1): 19–37. 2014.
What to expect when you are consolidating: effective prediction models of application performance on multicores [link]Paper   doi   link   bibtex  
Quantifying the Brown Side of Priority Schedulers: Lessons from Big Clusters. Çavdar, D.; Rosà, A.; Chen, L. Y.; Binder, W.; and Alagöz, F. SIGMETRICS Perform. Evaluation Rev., 42(3): 76–81. 2014.
Quantifying the Brown Side of Priority Schedulers: Lessons from Big Clusters [link]Paper   doi   link   bibtex  
Failure Analysis of Virtual and Physical Machines: Patterns, Causes and Characteristics. Birke, R.; Giurgiu, I.; Chen, L. Y.; Wiesmann, D.; and Engbersen, T. In 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2014, Atlanta, GA, USA, June 23-26, 2014, pages 1–12, 2014. IEEE Computer Society
Failure Analysis of Virtual and Physical Machines: Patterns, Causes and Characteristics [link]Paper   doi   link   bibtex  
(Big)data in a virtualized world: volume, velocity, and variety in cloud datacenters. Birke, R.; Björkqvist, M.; Chen, L. Y.; Smirni, E.; and Engbersen, T. In Schroeder, B.; and Thereska, E., editor(s), Proceedings of the 12th USENIX conference on File and Storage Technologies, FAST 2014, Santa Clara, CA, USA, February 17-20, 2014, pages 177–189, 2014. USENIX
(Big)data in a virtualized world: volume, velocity, and variety in cloud datacenters [link]Paper   link   bibtex  
Green MapReduce for heterogeneous data centers. Cavdar, D.; Chen, L. Y.; and Alagöz, F. In IEEE Global Communications Conference, GLOBECOM 2014, Austin, TX, USA, December 8-12, 2014, pages 1120–1126, 2014. IEEE
Green MapReduce for heterogeneous data centers [link]Paper   doi   link   bibtex  
ParSim: A Tool for Workload Modeling and Reproduction of Parallel Applications. Rosà, A.; Binder, W.; Chen, L. Y.; Gribaudo, M.; and Serazzi, G. In IEEE 22nd International Symposium on Modelling, Analysis & Simulation of Computer and Telecommunication Systems, MASCOTS 2014, Paris, France, September 9-11, 2014, pages 494–497, 2014. IEEE Computer Society
ParSim: A Tool for Workload Modeling and Reproduction of Parallel Applications [link]Paper   doi   link   bibtex  
Showstopper: The Partial CPU Load Tool. Podzimek, A.; Chen, L. Y.; Bulej, L.; Binder, W.; and Tuma, P. In IEEE 22nd International Symposium on Modelling, Analysis & Simulation of Computer and Telecommunication Systems, MASCOTS 2014, Paris, France, September 9-11, 2014, pages 510–513, 2014. IEEE Computer Society
Showstopper: The Partial CPU Load Tool [link]Paper   doi   link   bibtex  
Multi-resource characterization and their (in)dependencies in production datacenters. Birke, R.; Chen, L. Y.; and Smirni, E. In 2014 IEEE Network Operations and Management Symposium, NOMS 2014, Krakow, Poland, May 5-9, 2014, pages 1–6, 2014. IEEE
Multi-resource characterization and their (in)dependencies in production datacenters [link]Paper   doi   link   bibtex  
  2013 (8)
Join the Best Queue: Reducing Performance Variability in Heterogeneous Systems. Spicuglia, S.; Chen, L. Y.; and Binder, W. In 2013 IEEE Sixth International Conference on Cloud Computing, Santa Clara, CA, USA, June 28 - July 3, 2013, pages 139–146, 2013. IEEE Computer Society
Join the Best Queue: Reducing Performance Variability in Heterogeneous Systems [link]Paper   doi   link   bibtex  
State-of-the-practice in data center virtualization: Toward a better understanding of VM usage. Birke, R.; Podzimek, A.; Chen, L. Y.; and Smirni, E. In 2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), Budapest, Hungary, June 24-27, 2013, pages 1–12, 2013. IEEE Computer Society
State-of-the-practice in data center virtualization: Toward a better understanding of VM usage [link]Paper   doi   link   bibtex  
QoS-Aware Service VM Provisioning in Clouds: Experiences, Models, and Cost Analysis. Björkqvist, M.; Spicuglia, S.; Chen, L. Y.; and Binder, W. In Basu, S.; Pautasso, C.; Zhang, L.; and Fu, X., editor(s), Service-Oriented Computing - 11th International Conference, ICSOC 2013, Berlin, Germany, December 2-5, 2013, Proceedings, volume 8274, of Lecture Notes in Computer Science, pages 69–83, 2013. Springer
QoS-Aware Service VM Provisioning in Clouds: Experiences, Models, and Cost Analysis [link]Paper   doi   link   bibtex  
A datacenter network tale from a server's perspective. Birke, R.; Chen, L. Y.; and Minkenberg, C. In 21st IEEE/ACM International Symposium on Quality of Service, IWQoS 2013, Montreal, Canada, 3-4 June 2013, pages 99–108, 2013. IEEE
A datacenter network tale from a server's perspective [link]Paper   doi   link   bibtex  
Transforming System Load to Throughput for Consolidated Applications. Podzimek, A.; and Chen, L. Y. In 2013 IEEE 21st International Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems, San Francisco, CA, USA, August 14-16, 2013, pages 288–292, 2013. IEEE Computer Society
Transforming System Load to Throughput for Consolidated Applications [link]Paper   doi   link   bibtex  
Characterization Analysis of Resource Utilization Distribution. Birke, R.; Chen, L. Y.; Gribaudo, M.; and Piazzolla, P. In 2013 IEEE 21st International Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems, San Francisco, CA, USA, August 14-16, 2013, pages 370–374, 2013. IEEE Computer Society
Characterization Analysis of Resource Utilization Distribution [link]Paper   doi   link   bibtex  
On load balancing: a mix-aware algorithm for heterogeneous systems. Spicuglia, S.; Björkqvist, M.; Chen, L. Y.; Serazzi, G.; Binder, W.; and Smirni, E. In Seelam, S.; Tuma, P.; Casale, G.; Field, T.; and Amaral, J. N., editor(s), ACM/SPEC International Conference on Performance Engineering, ICPE'13, Prague, Czech Republic - April 21 - 24, 2013, pages 71–76, 2013. ACM
On load balancing: a mix-aware algorithm for heterogeneous systems [link]Paper   doi   link   bibtex  
Parallelism profiling and wall-time prediction for multi-threaded applications. Peternier, A.; Binder, W.; Yokokawa, A.; and Chen, L. Y. In Seelam, S.; Tuma, P.; Casale, G.; Field, T.; and Amaral, J. N., editor(s), ACM/SPEC International Conference on Performance Engineering, ICPE'13, Prague, Czech Republic - April 21 - 24, 2013, pages 211–216, 2013. ACM
Parallelism profiling and wall-time prediction for multi-threaded applications [link]Paper   doi   link   bibtex  
  2012 (9)
Opportunistic Service Provisioning in the Cloud. Björkqvist, M.; Chen, L. Y.; and Binder, W. In Chang, R., editor(s), 2012 IEEE Fifth International Conference on Cloud Computing, Honolulu, HI, USA, June 24-29, 2012, pages 237–244, 2012. IEEE Computer Society
Opportunistic Service Provisioning in the Cloud [link]Paper   doi   link   bibtex  
Data Centers in the Cloud: A Large Scale Performance Study. Birke, R.; Chen, L. Y.; and Smirni, E. In Chang, R., editor(s), 2012 IEEE Fifth International Conference on Cloud Computing, Honolulu, HI, USA, June 24-29, 2012, pages 336–343, 2012. IEEE Computer Society
Data Centers in the Cloud: A Large Scale Performance Study [link]Paper   doi   link   bibtex  
Dynamic Replication in Service-Oriented Systems. Björkqvist, M.; Chen, L. Y.; and Binder, W. In 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012, Ottawa, Canada, May 13-16, 2012, pages 531–538, 2012. IEEE Computer Society
Dynamic Replication in Service-Oriented Systems [link]Paper   doi   link   bibtex  
Deferred methods: accelerating dynamic program analysis on multicores. Ansaloni, D.; Binder, W.; Heydarnoori, A.; and Chen, L. Y. In Eidt, C.; Holler, A. M.; Srinivasan, U.; and Amarasinghe, S. P., editor(s), 10th Annual IEEE/ACM International Symposium on Code Generation and Optimization, CGO 2012, San Jose, CA, USA, March 31 - April 04, 2012, pages 242–251, 2012. ACM
Deferred methods: accelerating dynamic program analysis on multicores [link]Paper   doi   link   bibtex  
Model-driven consolidation of Java workloads on multicores. Ansaloni, D.; Chen, L. Y.; Smirni, E.; and Binder, W. In Swarz, R. S.; Koopman, P.; and Cukier, M., editor(s), IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2012, Boston, MA, USA, June 25-28, 2012, pages 1–12, 2012. IEEE Computer Society
Model-driven consolidation of Java workloads on multicores [link]Paper   doi   link   bibtex  
Achieving application-centric performance targets via consolidation on multicores: myth or reality?. Chen, L. Y.; Ansaloni, D.; Smirni, E.; Yokokawa, A.; and Binder, W. In Epema, D. H. J.; Kielmann, T.; and Ripeanu, M., editor(s), The 21st International Symposium on High-Performance Parallel and Distributed Computing, HPDC'12, Delft, Netherlands - June 18 - 22, 2012, pages 37–48, 2012. ACM
Achieving application-centric performance targets via consolidation on multicores: myth or reality? [link]Paper   doi   link   bibtex  
Usage patterns in multi-tenant data centers: a temporal perspective. Birke, R.; Chen, L. Y.; and Smirni, E. In Milojicic, D. S.; Xu, D.; and Talwar, V., editor(s), 9th International Conference on Autonomic Computing, ICAC'12, San Jose, CA, USA, September 16 - 20, 2012, pages 161–166, 2012. ACM
Usage patterns in multi-tenant data centers: a temporal perspective [link]Paper   doi   link   bibtex  
Cost-driven service provisioning in hybrid clouds. Björkqvist, M.; Chen, L. Y.; and Binder, W. In 2012 Fifth IEEE International Conference on Service-Oriented Computing and Applications (SOCA), Taipei, Taiwan, December 17-19, 2012, pages 1–8, 2012. IEEE Computer Society
Cost-driven service provisioning in hybrid clouds [link]Paper   doi   link   bibtex  
Find your best match: predicting performance of consolidated workloads. Ansaloni, D.; Chen, L. Y.; Smirni, E.; Yokokawa, A.; and Binder, W. In Kaeli, D. R.; Rolia, J.; John, L. K.; and Krishnamurthy, D., editor(s), Third Joint WOSP/SIPEW International Conference on Performance Engineering, ICPE'12, Boston, MA, USA - April 22 - 25, 2012, pages 243–244, 2012. ACM
Find your best match: predicting performance of consolidated workloads [link]Paper   doi   link   bibtex  
  2011 (5)
Minimizing Retrieval Cost of Multi-Layer Content Distribution Systems. Björkqvist, M.; Chen, L. Y.; and Zhang, X. In Proceedings of IEEE International Conference on Communications, ICC 2011, Kyoto, Japan, 5-9 June, 2011, pages 1–6, 2011. IEEE
Minimizing Retrieval Cost of Multi-Layer Content Distribution Systems [link]Paper   doi   link   bibtex  
Minimizing retrieval latency for content cloud. Björkqvist, M.; Chen, L. Y.; Vukolic, M.; and Zhang, X. In INFOCOM 2011. 30th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, 10-15 April 2011, Shanghai, China, pages 1080–1088, 2011. IEEE
Minimizing retrieval latency for content cloud [link]Paper   doi   link   bibtex  
On the convergence to fairness in overloaded FIFO systems. Ciucu, F.; Hohlfeld, O.; and Chen, L. Y. In INFOCOM 2011. 30th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, 10-15 April 2011, Shanghai, China, pages 1988–1996, 2011. IEEE
On the convergence to fairness in overloaded FIFO systems [link]Paper   doi   link   bibtex  
Towards realizing a low cost and highly available datacenter power infrastructure. Govindan, S.; Wang, D.; Chen, L. Y.; Sivasubramaniam, A.; and Urgaonkar, B. In Bianchini, R.; and Dutta, P., editor(s), Proceedings of the 4th Workshop on Power-Aware Computing and Systems, HotPower '11, Cascais, Portugal, October 23, 2011, pages 7:1–7:5, 2011. ACM
Towards realizing a low cost and highly available datacenter power infrastructure [link]Paper   doi   link   bibtex  
Optimizing service replication in clouds. Björkqvist, M.; Chen, L. Y.; and Binder, W. In Jain, S.; Jr., R. R. C.; Himmelspach, J.; White, K. P.; and Fu, M. C., editor(s), Winter Simulation Conference 2011, WSC'11, Phoenix, AZ, USA, December 11-14, 2011, pages 3312–3322, 2011. IEEE
Optimizing service replication in clouds [link]Paper   doi   link   bibtex  
  2010 (4)
End-to-end congestion management for non-blocking multi-stage switching fabrics. Chrysos, N.; Chen, L. Y.; Minkenberg, C.; Kachris, C.; and Katevenis, M. In Lin, B.; Mogul, J. C.; and Iyer, R. R., editor(s), Proceedings of the 2010 ACM/IEEE Symposium on Architecture for Networking and Communications Systems, ANCS 2010, San Diego, California, USA, October 25-26, 2010, pages 6, 2010. ACM
End-to-end congestion management for non-blocking multi-stage switching fabrics [link]Paper   doi   link   bibtex  
Throughput of random arbitration for approximate matchings. Chen, L. Y.; and Chrysos, N. In Lin, B.; Mogul, J. C.; and Iyer, R. R., editor(s), Proceedings of the 2010 ACM/IEEE Symposium on Architecture for Networking and Communications Systems, ANCS 2010, San Diego, California, USA, October 25-26, 2010, pages 16, 2010. ACM
Throughput of random arbitration for approximate matchings [link]Paper   doi   link   bibtex  
Load-Balancing Dynamic Service Binding in Composition Execution Engines. Björkqvist, M.; Chen, L. Y.; and Binder, W. In 5th IEEE Asia-Pacific Services Computing Conference, APSCC 2010, 6-10 December 2010, Hangzhou, China, Proceedings, pages 67–74, 2010. IEEE Computer Society
Load-Balancing Dynamic Service Binding in Composition Execution Engines [link]Paper   doi   link   bibtex  
Content Retrieval Delay Driven by Caching Policy and Source Selection. Björkqvist, M.; and Chen, L. Y. In MASCOTS 2010, 18th Annual IEEE/ACM International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, Miami, Florida, USA, August 17-19, 2010, pages 397–399, 2010. IEEE Computer Society
Content Retrieval Delay Driven by Caching Policy and Source Selection [link]Paper   doi   link   bibtex  
  2009 (3)
Caching Video Contents in IPTV Systems with Hierarchical Architecture. Chen, L. Y.; Meo, M.; and Scicchitano, A. In Proceedings of IEEE International Conference on Communications, ICC 2009, Dresden, Germany, 14-18 June 2009, pages 1–6, 2009. IEEE
Caching Video Contents in IPTV Systems with Hierarchical Architecture [link]Paper   doi   link   bibtex  
Server Frequency Control Using Markov Decision Processes. Chen, L. Y.; and Gautam, N. In INFOCOM 2009. 28th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, 19-25 April 2009, Rio de Janeiro, Brazil, pages 2951–2955, 2009. IEEE
Server Frequency Control Using Markov Decision Processes [link]Paper   doi   link   bibtex  
Optimization of link bandwidth for parallel communication performance. Chen, L. Y.; Denzel, W. E.; and Luijten, R. P. In 28th International Performance Computing and Communications Conference, IPCCC 2009, 14-16 December 2009, Phoenix, Arizona, USA, pages 137–144, 2009. IEEE Computer Society
Optimization of link bandwidth for parallel communication performance [link]Paper   doi   link   bibtex  
  2006 (2)
A first-principles based LPV modeling and design for performance management of Internet Web servers. Qin, W.; Wang, Q.; Chen, Y.; and Gautam, N. In American Control Conference, ACC 2006, Minneapolis, MN, USA, 14-16 June, 2006, pages 1–6, 2006. IEEE
A first-principles based LPV modeling and design for performance management of Internet Web servers [link]Paper   doi   link   bibtex  
Consolidating clients on back-end servers with co-location and frequency control. Chen, Y.; Das, A.; Sivasubramaniam, A.; Wang, Q.; Harper, R.; and Bland, M. In Marie, R. A.; Key, P. B.; and Smirni, E., editor(s), Proceedings of the Joint International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS/Performance 2006, Saint Malo, France, June 26-30, 2006, pages 383–384, 2006. ACM
Consolidating clients on back-end servers with co-location and frequency control [link]Paper   doi   link   bibtex   1 download  
  2005 (1)
Managing server energy and operational costs in hosting centers. Chen, Y.; Das, A.; Qin, W.; Sivasubramaniam, A.; Wang, Q.; and Gautam, N. In Eager, D. L.; Williamson, C. L.; Borst, S. C.; and Lui, J. C. S., editor(s), Proceedings of the International Conference on Measurements and Modeling of Computer Systems, SIGMETRICS 2005, June 6-10, 2005, Banff, Alberta, Canada, pages 303–314, 2005. ACM
Managing server energy and operational costs in hosting centers [link]Paper   doi   link   bibtex  
  2004 (2)
Pricing-based strategies for autonomic control of web servers for time-varying request arrivals. Chen, Y.; Das, A.; Gautam, N.; Wang, Q.; and Sivasubramaniam, A. Eng. Appl. Artif. Intell., 17(7): 841–854. 2004.
Pricing-based strategies for autonomic control of web servers for time-varying request arrivals [link]Paper   doi   link   bibtex  
Pricing and Autonomic Control of Web Servers with Time-Varying Request Patterns. Chen, Y.; Das, A.; Gautam, N.; Wang, Q.; and Sivasubramaniam, A. In 1st International Conference on Autonomic Computing (ICAC 2004), 17-19 May 2004, New York, NY, USA, pages 290–291, 2004. IEEE Computer Society
Pricing and Autonomic Control of Web Servers with Time-Varying Request Patterns [link]Paper   doi   link   bibtex