Conference Papers (recent)

Google Scholar Profile

2022

  1. Z. Shao, J. Yang, C. Shen and S. Ren, “Learning for Robust Combinatorial Optimization: Algorithm and Application”, IEEE Conference on Computer Communications (INFOCOM 2022), May 2022 (acceptance rate: 19.9%)

2021

  1. C. Shi, H. Xu, W. Xiong, and C. Shen, “(Almost) Free Incentivized Exploration from Decentralized Learning Agents,” Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), Dec. 2021 (acceptance rate: 26%)

  2. C. Shi, W. Xiong, C. Shen, and J. Yang, “Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization,” Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), Dec. 2021 (acceptance rate: 26%)

  3. R. Huang, W. Wu, J. Yang, and C. Shen, “Federated Linear Contextual Bandits,” Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), Dec. 2021 (acceptance rate: 26%)

  4. Y. Mu, Y. Tan, M. Veeraraghavan, and C. Shen, “A Machine Learning Approach for Rate Prediction in Multicast File-stream Distribution Networks,” IEEE Global Communications Conference (GLOBECOM), 2021

  5. C. Shi and C. Shen, “An Attackability Perspective on No-Sensing Adversarial Multi-player Multi-armed Bandits,” IEEE International Symposium on Information Theory (ISIT), July 2021

  6. X. Wei and C. Shen, “Federated Learning over Noisy Channels,” IEEE International Conference on Communications (ICC), June 2021

  7. C. Shen, P. Zhao, and X. Luo, “On Energy Efficient Uplink Multi-User MIMO with Shared LNA Control,” IEEE International Conference on Communications (ICC), June 2021

  8. S. Zheng, C. Shen, and X. Chen, “Design and Analysis of Uplink and Downlink Communications for Federated Learning,” IEEE International Conference on Communications (ICC), June 2021 (Best Paper Award)

  9. H. Lee, C. Shen, W. Zame, J. Lee, and M. van der Schaar, “SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups,” The 24rd International Conference on Artificial Intelligence and Statistics (AISTATS), Apr. 2021

  10. C. Shi, C. Shen, and J. Yang, “Federated Multi-armed Bandits with Personalization,” The 24rd International Conference on Artificial Intelligence and Statistics (AISTATS), Apr. 2021 (Oral Presentation, 48/1527 = 3%) [Code]

  11. C. Shi and C. Shen, “Federated Multi-Armed Bandits,” The 35th AAAI Conference on Artificial Intelligence (AAAI), Feb. 2021 [Code] (acceptance rate: 21.4%)

2020

  1. H.-S. Lee, Y. Zhang, W. Zame, C. Shen, J.-W. Lee, and M. van der Schaar, “Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty Quantification,” The Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), Dec. 2020 (acceptance rate: 20.1%)

  2. C. Shen and S. Chen, “Federated Learning with Heterogeneous Quantization,” ACM/IEEE Symposium on Edge Computing - Workshop on Edge Computing and Communications (EdgeComm), Nov. 2020

  3. C. Shen, D. Li, and J. Yang, “MIMO Receive Antenna Selection via Deep Learning and Greedy Adaptation,” The 54th Asilomar Conference on Signals, Systems and Computers, Nov. 2020 (Invited Paper)

  4. C. Gan, J. Yang, and C. Shen, “Thresholded Wirtinger Flow for Fast Millimeter Wave Beam Alignment,” The 54th Asilomar Conference on Signals, Systems and Computers, Nov. 2020 (Invited Paper)

  5. C. Shen, Z. Wang, S. Villa, and M. van der Schaar, “Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints,” The 37th International Conference on Machine Learning (ICML), July 2020 (acceptance rate: 21.8%)

  6. W. Chen, R. Zhou, C. Tian, and C. Shen, “On Top-k Selection from m-wise Partial Rankings via Borda Counting,” IEEE International Symposium on Information Theory (ISIT), June 2020

  7. K. Yang, C. Shen, and T. Liu, “Deep Reinforcement Learning based Wireless Network Optimization: A Comparative Study,” IEEE INFOCOM 2020 Workshop on Data Driven Intelligence for Networks, July 2020 (selected for journal fast track)

  8. H. Lee, C. Shen, J. Jordon, and M. van der Schaar, “Contextual Constrained Learning for Dose-Finding Clinical Trials,” The 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), Aug. 2020

  9. C. Shi, W. Xiong, C. Shen, and J. Yang, “Decentralized Multi-player Multi-armed Bandits with No Collision Information,” The 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), Aug. 2020

  10. W. Wu, J. Yang, and C. Shen, “Stochastic Linear Contextual Bandits with Diverse Contexts,” The 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), Aug. 2020

2019

  1. C. Shi, L. Chen, C. Shen, and J. Xu, “Privacy-Aware Edge Computing Based on Adaptive DNN Partitioning,” IEEE GLOBECOM, Dec. 2019

  2. C. Wang, R. Zhou, J. Yang, C. Shen, “A Cascading Bandit Approach to Efficient Mobility Management in Ultra-Dense Networks,” IEEE International Workshop on Machine Learning for Signal Processing, Oct. 2019 (Invited Paper)

  3. F. Liang, C. Shen, W. Yu, and F. Wu, “Power Control for Interference Management via Ensembling Deep Neural Networks,” IEEE/CIC ICCC 2019, Changchun, China, Aug. 2019 (Invited Paper)

  4. C. Gan, J. Yang, R. Zhou, and C. Shen, “Online Learning with Diverse User Preferences,” IEEE International Symposium on Information Theory, Paris, France, July 2019

2018

  1. H. Zhang and C. Shen, “Best Arm Identification for Both Stochastic and Adversarial Multi-armed Bandits,” IEEE Information Theory Workshop (ITW) 2018, Guangzhou, China, Nov. 2018 (Invited Paper)

  2. Z. Wang, Z. Ying, and C. Shen, “Opportunistic Spectrum Access via Good Arm Identification,” IEEE GlobalSIP 2018, Anaheim, California, USA, Nov. 2018

  3. J. Yang, C. Wang, X. Wang, and C. Shen, “A Machine Learning Approach to User Association in Enterprise Small Cell Networks,” IEEE/CIC ICCC 2018, Beijing, China, Aug. 2018 (Invited Paper)

  4. R. Zhou, C. Gan, J. Yang, and C. Shen, “Cost-aware Cascading Bandits,” in Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18), Pages 3228-3234, July 2018 (acceptance rate: 20.5%)

  5. S. Shao, T. Liu, C. Tian, and C. Shen, “New Results On Multilevel Diversity Coding with Secure Regeneration,” IEEE International Symposium on Information Theory (ISIT), 2018

  6. Z. Wang, R. Zhou, and C. Shen, “Regional Multi-Armed Bandits,” in Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AISTATS), Playa Blanca, Lanzarote, Canary Islands, April 9-11, 2018

  7. Z. Wang and C. Shen, “Small Cell Power Assignment with Unimodal Continuum-armed Bandit Learning,” IEEE ICC 2018 Workshop on 5G-UDN

  8. K. Liu, C. Shen, S. Chattopadhyay, and H. Dai, “Designing Interdependent Networks Against Cascading Failures with Node Protections,” IEEE ICC 2018

  9. Y. Zhou, C. Shen, X. Luo, and M. van der Schaar, “A Non-Stationary Online Learning Approach to Mobility Management,” IEEE ICC 2018

  10. F. Liang, C. Shen, and F. Wu, “Exploiting Noise Correlation for Channel Decoding with Convolutional Neural Networks,” IEEE ICC 2018

  11. H. Wu, L, Chen, C. Shen, W. Wen, and J. Xu, “Online Geographical Load Balancing for Energy-Harvesting Mobile Edge Computing,” IEEE ICC 2018

  12. F. Yang, H. Zhu, C. Shen, L. Dai, and X. Luo, “How to Interconnect for Massive MIMO Self-Calibration?” IEEE ICASSP, Calgary, Canada, April 2018

  13. J. Dai and C. Shen, “Adaptive Resource Allocation for LTE/WiFi Coexistence in the Unlicensed Spectrum,” IEEE ICNC, March 2018

2017

  1. J. Dai and C. Shen, “A Modified LBT Mechanism and Performance Enhancement for LTE-U/WiFi Co-Existence,” IEEE/CIC ICCC 2017

  2. X. Luo, P. Cai, X. Zhang, C. Shen, and H. Qian, “Aligning DL Paths for Scalable CSI Feedback in FDD Massive MIMO,” in Proc. International Wireless Communications and Mobile Computing Conference (IWCMC), Valencia, Spain, June 26-30, 2017

  3. X. Luo, X. Zhang, P. Cai, C. Shen, D. Hu, and H. Qian, “DL CSI Acquisition and Feedback in FDD Massive MIMO via Path Aligning,” in the 9th International Conference on Ubiquitous and Future Networks, July 2017 (Excellent Paper Award)

  4. S. Shao, T. Liu, C. Tian, and C. Shen, “On the Tradeoff Region of Secure Exact-Repair Regenerating Codes,” IEEE International Symposium on Information Theory (ISIT), Germany, June 2017

  5. H. Wu, C. Shen, and S. Chen, “On Scheduling Policies in the Presence of Heavy-Tailed Interference,” Proc. Information Theory and Applications (ITA) Workshop, La Jolla, CA, USA, Feb. 2017