Books

  1. L. Huang, “Learning for Decision and Control in Stochastic Networks”, Synthesis Lectures on Learning, Networks, and Algorithms, Springer Nature, June 2023.

  2. (Chinese) A. Yao (Editor), L. Huang (Vice Editor), Y. Gao, J. Li, X. Ma, Y. Wu, Y. Yuan, C. Zhang, H. Zhao, “Artificial Intelligence" (人工智能), Tsinghua University Press, September 2022. (清华出版社2022年十佳图书)

  3. (Chinese) A. Yao (Editor), L. Huang (Vice Editor), Y. Gao, J. Li, X. Ma, W. Wu, Y. Wu, Y. Yuan, C. Zhang, “Artificial Intelligence (High School)" (人工智能(高中版)), Tsinghua University Press, May 2021.

  4. (Translation) L. Huang, “Probability in Electrical Engineering and Computer Science: An Application-Driven Course” by Prof. Jean Walrand, Turing Book Company, September 2015. [The original version can be found here]

Conference Papers:

  1. Yan Dai, Longbo Huang, ‘‘Adversarial Network Optimization under Bandit Feedback: Maximizing Utility in Non-Stationary Multi-Hop Networks,’’ Proceedings of ACM Sigmetrics (Sigmetrics), June 2025.

  2. Pihe Hu, Shoaling Li, Zhuoran Li, Ling Pan, Longbo Huang, ‘‘Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training,’’ Proceedings of the Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), December 2024.

  3. Zhuoran Li, Pihe Hu, Longbo Huang, “Offline Learning-based Multi-User Delay-Constrained Scheduling,” Proceedings of the 21st IEEE International Conference on Mobile Ad Hoc and Smart Systems (MASS), September 2024. (Invited Paper)

  4. Boning Li, Zhixuan Fang, Longbo Huang, “RL-CFR: Improving Action Abstraction for Imperfect Information Extensive-Form Games with Reinforcement Learning,” Proceedings of the Forty-first International Conference on Machine Learning (ICML), July 2024.

  5. Yu Chen, Xiangcheng Zhang, Siwei Wang, Longbo Huang, “Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation,” Proceedings of the Forty-first International Conference on Machine Learning (ICML), July 2024.

  6. Tonghe Zhang, Yu Chen, Longbo Huang, “Provably Efficient Partially Observable Risk-sensitive Reinforcement Learning with Hindsight Observation,” Proceedings of the Forty-first International Conference on Machine Learning (ICML), July 2024.

  7. Yu Chen, Yihan Du, Pihe Hu, Siwei Wang, Desheng Wu, Longbo Huang, “Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback,” Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024.

  8. Xinran Gu, Kaifeng Lyu, Sanjeev Arora, Jingzhao Zhang, Longbo Huang, “A Quadratic Synchronization Rule for Distributed Deep Learning,” Proceedings of the Twelfth International Conference on Learning Representations (ICLR), May 2024.

  9. Nuoya Xiong, Yihan Du, Longbo Huang, “Provably Safe Reinforcement Learning with Step-wise Violation Constraints,” Proceedings of the Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), December 2023.

  10. Jiatai Huang, Yan Dai, Longbo Huang, “Banker Online Mirror Descent: A Universal Approach for Delayed Online Bandit Learning,” Proceedings of the Fortieth International Conference on Machine Learning (ICML), July 2023.

  11. Yihan Du, Longbo Huang, Wen Sun, “Multi-task Representation Learning for Pure Exploration in Linear Bandits,” Proceedings of the Fortieth International Conference on Machine Learning (ICML), July 2023.

  12. Ling Pan, Dinghuai Zhang, Moksh Jain, Longbo Huang, Yoshua Bengio, “Stochastic Generative Flow Networks ,” Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI), July 2023. (Spotlight)

  13. Yiqin Tan, Pihe Hu, Ling Pan, Jiatai Huang, Longbo Huang, “RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch,” Proceedings of the Eleventh International Conference on Learning Representations (ICLR), May 2023. (Spotlight)

  14. Ling Pan, Dinghuai Zhang, Aaron Courville, Longbo Huang, Yoshua Bengio, “Generative Augmented Flow Networks,” Proceedings of the Eleventh International Conference on Learning Representations (ICLR), May 2023. (Spotlight)

  15. Xinran Gu, Kaifeng Lyu, Longbo Huang, Sanjeev Arora, “Why (and When) does Local SGD Generalize Better than SGD?,” Proceedings of the Eleventh International Conference on Learning Representations (ICLR), May 2023.

  16. Yihan Du, Siwei Wang, Longbo Huang, “Provably Efficient Risk-Sensitive Reinforcement Learning: Iterated CVaR and Worst Path,” Proceedings of the Eleventh International Conference on Learning Representations (ICLR), May 2023.

  17. Yihan Du, Wei Chen, Yuko Kuroki, Longbo Huang, “Collaborative Pure Exploration in Kernel Bandit,” Proceedings of the Eleventh International Conference on Learning Representations (ICLR), May 2023.

  18. Pihe Hu, Yu Chen, Longbo Huang, “Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs,” Proceedings of the Eleventh International Conference on Learning Representations (ICLR), May 2023.

  19. Y. Cai, C. Zhang, W. Shen, X. Zhang, W. Ruan, L. Huang, “RePreM: Representation Pre-training with Masked Model for Reinforcement Learning,” Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), February 2023.

  20. Y. Huang, Y. Liang, and L. Huang, “Provable Generalization of Overparameterized Meta-learning Trained with SGD,” Proceedings of the Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), December 2022. (Spotlight)

  21. X. Gu, K. Lyu, L. Huang, S. Arora, “Why (and When) does Local SGD Generalize Better than SGD?,” The 14th International OPT Workshop on Optimization for Machine Learning (NeurIPS-OPT), December 2022.

  22. Y. Huang, Y. Cheng, Y. Liang, L. Huang, “Online Min-max Optimization: Nonconvexity,” The 14th International OPT Workshop on Optimization for Machine Learning (NeurIPS-OPT), December 2022.

  23. Y. Cai, C. Zhang, W. Shen, X. He, X. Zhang and L. Huang, ‘‘Imitation Learning to Outperform Demonstrators by Directly Extrapolating Demonstrations,’’ Proceedings of the 31st ACM International Conference on Information and Knowledge Management, (CIKM), October 2022.

  24. P. Hu, L. Pan, Y.Chen, Z. Fang, L.Huang, “Effective Multi-User Delay-Constrained Scheduling with Deep Recurrent Reinforcement Learning,” Proceedings of the 23rd ACM International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (MobiHoc), October 2022.

  25. L. Pan, L. Huang, T. Ma, H. Xu, “Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification,” Proceedings of the 39th International Conference on Machine Learning (ICML), July 2022.

  26. P. Hu, Y. Chen, L. Huang, “Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation,” Proceedings of the 39th International Conference on Machine Learning (ICML), July 2022.

  27. Y. Huang, J. Lin, C. Zhou, H. Yang, L. Huang, “Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably),” Proceedings of the 39th International Conference on Machine Learning (ICML), July 2022.

  28. J. Huang, Y. Dai, L. Huang, “Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits,” Proceedings of the 39th International Conference on Machine Learning (ICML), July 2022.

  29. T. Jin, L. Huang, H. Luo, “The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition,” Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), December 2021. (Oral, top 1%)

  30. Y. Huang, C. Du, Z. Xue, X. Chen, H. Zhao, L. Huang, ‘‘What Makes Multimodal Learning Better than Single (Provably),’’ Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), December 2021.

  31. X. Gu, K. Huang, J. Zhang, L. Huang, “Fast Federated Learning in the Presence of Arbitrary Device Unavailability,” Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), December 2021.

  32. Y. Du, S. Wang, Z. Fang, L. Huang, “Continuous Mean-Covariance Bandits,” Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), December 2021.

  33. L. Pan, T. Rshid, B. Peng, L. Huang, S. Whiteson, “Regularized Softmax Deep Multi-Agent Q-Learning,” Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), December 2021.

  34. Y. Lin, G. Qu, L. Huang, A. Wierman, “Multi-Agent Reinforcement Learning in Stochastic Networked Systems,” Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), December 2021.

  35. L. Pan, L. Huang, T. Ma, H. Xu, “Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification,” NeurIPS Deep Reinforcement Learning Workshop (NeurIPS-WDRL), December 2021.

  36. Q. Liu, W. Wu, L. Huang, Z. Fang, “Simultaneously Achieving Sublinear Regret and Constraint Violations for Online Convex Optimization with Time-varying Constraints,” Proceedings of the 39th International Symposium on Computer Performance, Modeling, Measurements and Evaluation (Performance), November 2021.

  37. J. Huang and L. Huang, “Robust Wireless Scheduling under Arbitrary Channel Dynamics and Feedback Delay,” Proceedings of International Teletraffic Congress (ITC), August 2021. (Invited Paper)

  38. T. Jin, L. Huang, H. Luo, “The Best of Both Worlds: Stochastic and Adversarial Episodic MDPs with Unknown Transition,” ICML-Workshop on Reinforcement Learning Theory (ICML-WRLT), July 2021.

  39. Y. Du, S. Wang, L. Huang, “A One-Size-Fits-All Solution to Conservative Bandit Problems,” Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), February 2021.

  40. S. Wang, H. Wang, L. Huang, “Adaptive Algorithms for Multi-armed Bandit with Composite and Anonymous Feedback,” Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), February 2021.

  41. C. Zhang, Y. Cai, L. Huang, J. Li, “Exploration by Maximizing Renyi Entropy for Reward-Free RL Framework,” Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), February 2021.

  42. L. Pan, Q. Cai and L. Huang, ‘‘Softmax Deep Double Deterministic Policy Gradients,’’ Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), December 2020.

  43. S. Wang, L. Huang, and J. C. S. Lui, ‘‘Restless-UCB, an Efficient and Low-complexity Algorithm for Online Restless Bandits,’’ Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), December 2020.

  44. Y. Huang, L. Huang, “Heavy Traffic Analysis of Approximate Max-Weight Matching Algorithms for Input-Queued Switches,” Proceedings of the 38th International Symposium on Computer Performance, Modeling, Measurements and Evaluation (Performance), November 2020.

  45. W. Chen, Y. Du, L. Huang, H. Zhao, “Combinatorial Pure Exploration for Dueling Bandit,” Proceedings of the 2020 International Conference on Machine Learning (ICML), July 2020.

  46. L. Pan, Q. Cai, Q. Meng, W. Chen, L. Huang, “Reinforcement Learning with Dynamic Boltzmann Softmax Updates,” Proceedings of International Joint Conference on Artificial Intelligence –Pacific Rim International Conference on Artificial Intelligence (IJCAI), July 2020.

  47. L. Huang, Y. Li, J. Walrand, ‘‘RTCP - Reduce Delay Variability with an End-to-end Approach,’’ Proceedings of the International Federation for Information Processing (IFIP) Networking 2020 Conference (NETWORKING), June 2020.

  48. Y. Li, H. Zheng, C. Huang, K. Pei, J. Li, L. Huang, ‘‘Terminator: An Efficient and Light-weight Fault Localization Framework,’’ Proceedings of the IEEE International Workshop on Intelligent Cloud Computing and Networking at INFOCOM (INFOCOM-ICCN), 2020.

  49. L. Pan, Q. Cai and L. Huang, ‘‘Multi-Path Policy Optimization,’’ Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2020. (Selected for fast-track publication at JAAMAS, top 5%)

  50. Y. Du, S. Wang and L. Huang, ‘‘Dueling Bandits: From Two-dueling to Multi-dueling,’'Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2020.

  51. Y. Yu, J. Wu and L. Huang, ‘‘Double Quantization for Communication-Efficient Distributed Optimization,’’ Proceedings of the Thirty-third Conference on Neural Information Processing Systems (NeurIPS), December 2019.

  52. L. Pan, Q. Can, Z. Fang, P. Tang, and L. Huang, “A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems,” Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), Jan 2019. [arXiv Technical Report arXiv:1802.04592]

  53. S. Wang and L. Huang, “Multi-armed Bandits with Compensation,” Proceedings of the Thirty-second Conference on Neural Information Processing Systems (NIPS), December 2018.

  54. K. Chen, K. Cai, L. Huang, and J. C. S. Lui, “Beyond the Click-Through Rate: Web Link Selection with Multi-level Feedback,” Proceedings of the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI), July 2018.

  55. T. Hao and L. Huang, “A Social Interaction Activity based Time-Varying User Vectorization Method for Online Social Networks,” Proceedings of the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI), July 2018.

  56. Z. Fang, L. Huang, and A. Wierman, “Loyalty Programs in the Sharing Economy: Optimality and Competition,” Proceedings of the 19th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), June 2018.

  57. K. Chen and L. Huang, “Timely-Throughput Optimal Scheduling with Prediction,” IEEE International Conference on Computer Communications (INFOCOM), April 2018. (Invited for Fast-track Review at IEEE TNSE (7 out of 312 accepted papers were invited))

  58. K. Cai, K. Chen, L. Huang, and J. C. S. Lui, ‘‘Multi-level Feedback Web Links Selection Problem: Learning and Optimization,’’ Proceedings of IEEE International Conference on Data Mining series (ICDM) (short paper), November 2017.

  59. Y. Yu and L.Huang, ‘‘Fast Stochastic Variance Reduced ADMM for Stochastic Composition Optimization,’’ Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI) (full paper), August 2017.

  60. L.Huang, M. Chen, and Y. Liu, ‘‘Learning-aided Stochastic Network Optimization with Imperfect State Prediction,’’ Proceedings of the 18th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), July 2017.

  61. Z. Fang, L.Huang, and A. Wierman, ‘‘Prices and Subsidies in the Sharing Economy,’’ Proceedings of World Wide Web (WWW) (full paper), April 2017.

  62. T. Hao, J. Zhou, Y. Cheng, L. Huang, and H. Wu, ‘‘User Identification in Cyber-Physical Space: a Case Study on Mobile Query Logs and Trajectories,’’ Proceedings of ACM SigSpatial (SigSpatial) (Short Paper), Nov 2016.

  63. Z. Fang and L. Huang, ‘‘ Market Share Analysis with Brand Effect,’’ Proceedings of IEEE Conference on Decision and Control (CDC), Dec 2016.

  64. X. Chen, T. Chen, X. Wang, L. Huang, G. B. Giannakis, ‘‘Two-Scale Stochastic Control for Smart-Grid Powered Coordinated Multi-Point Systems,’’ Proceedings of IEEE Global Communications Conference (Globecom), Dec 2016.

  65. M. Hajiesmaili, C. Chau, M. Chen, and L. Huang, ‘‘Online Microgrid Energy Generation Scheduling Revisited: The Benefits of Randomization and Interval Prediction,’’ Proceedings of ACM e-Energy (e-Energy), June 2016. (Best Paper Runner-up)

  66. K. Chen and L. Huang, ‘‘Age-of-Information in the Presence of Error,’’ Proceedings of IEEE International Symposium on Information Theory (ISIT), July 2016.

  67. L. Huang, “System Intelligence: Model, Bounds and Algorithms,” Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), July 2016.

  68. T. Zhang, H. Wu, X. Liu and L. Huang, “Learning-Aided Scheduling for Mobile Virtual Network Operators with QoS Constraints,” Proceedings of the 14th Int. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), May 2016.

  69. G. Wang, S. Wang, B. Luo, X. Jin, Y. Zhu, W. Yang, L. Huang, W. Shi, D. Hu, and W. Xu, ‘‘Increasing Large-Scale Data Center Capacity by Statistical Power Control,’’ Proceedings of EuroSys (EuroSys), April 2016.

  70. Z. Fang and L. Huang, ‘‘Market Share Analysis with Brand Effect,’’ Proceedings of AAMAS (AAMAS) (Extended abstract), May 2016.

  71. L. Huang, ‘‘Fast-Convergent Learning-aided Control in Energy Harvesting Networks,’’ Proceedings of IEEE Conference on Decision and Control (CDC), Dec 2015.

  72. L. Huang, ‘‘Receding Learning-aided Control in Stochastic Networks,’’ IFIP Performance (Performance), Oct 2015.

  73. Y. Yan, S. He, Y. Liu and L. Huang, ‘‘Optimizing Power Consumption of Mobile Games,’’ Proceedings of the Workshop on Power-Aware Computing and Systems (HotPower), (In conjunction with ACM SOSP (SOSP)), October 2015.

  74. L. Huang, ‘‘The Value-of-Information in Matching with Queues,’’ Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), June 2015.

  75. L. Huang and E. Modiano, “Optimizing Age-of-Information in a Multi-class Queueing System,” Proceedings of IEEE International Symposium on Information Theory (ISIT), June 2015.

  76. S. Zhang, L. Huang, M. Chen, and X. Liu, ‘‘Proactive Serving Decreases User Delay Exponentially,’’ Proceedings of ACM MAMA (MAMA), (in conjunction with ACM Sigmetrics (Sigmetrics)), June 2015.

  77. B. Mak, M. Chen, G. Zhang, L. Huang, and H. Zeng, ‘‘Online Energy Management Strategy for Hybrid Electric Vehicle,’’ Proceedings of ACM e-Energy (eEnergy) (poster paper), July 2015.

  78. L. Huang, ‘‘Optimizing Your Online Advertisement Asynchronously,’’ Proceedings of IEEE Conference on Decision and Control (CDC), Dec 2014. [ArXiv Technical Report, arXiv:1403.5768v1]

  79. S. Supittayapornpong, L. Huang and M. J. Neely, ‘‘Time-Average Optimization with Nonconvex Decision Set and its Convergence,’’ Proceedings of IEEE Conference on Decision and Control (CDC), Dec 2014.

  80. H. Yu, M. Cheung, L. Huang and J. Huang, ‘‘Delay-Aware Predictive Network Selection in Data Offloading,’’ Proceedings of IEEE Global Communication Conference (Globecom), Dec 2014.

  81. L. Huang, S. Zhang, M. Chen, and X. Liu ‘‘When Backpressure meets Predictive Scheduling,’’ Proceedings of 15th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), August 2014. (Best Paper Candidate) [ArXiv Technical Report, arXiv:1309.1110v1]

  82. L. Huang, X. Liu, and X. Hao, ‘‘The Power of Online Learning in Stochastic Network Optimization,’’ Proceedings of ACM Sigmetrics (Sigmetrics) (full paper), June 2014. [Note: In this version, we revised the proof of Lemma 1 in the camera-ready paper. The result is now more general and does not require convexity of the functions.]

  83. L. Ai, X. Wu, L. Huang, L. Huang, P. Tang, and J. Li, ‘‘The Multi-shop Ski Rental Problem,’’ Proceedings of ACM Sigmetrics (Sigmetrics) (full paper), June 2014.

  84. S. Zhang, L. Huang, M. Chen, and X. Liu, ‘‘Proactive Serving Reduces User Delay Exponentially,’’ Proceedings of ACM Sigmetrics (Sigmetrics) (poster paper), June 2014.

  85. N. Edalat, M. Motani, J. Walrand and L. Huang, ‘‘Control of Systems that Store Renewable Energy,’’ Proceedings of ACM eEnergy (eEnergy), 2014.

  86. S. Chen, U. C. Kozat, L. Huang, G. Liang, X. Liu, Y. Sun, and N. B. Shroff, ‘‘When Queueing Meets Coding: Optimal-Latency Data Retrieving Scheme in Storage Clouds,’’ Proceedings of IEEE International Conference on Computer Communications (INFOCOM), April 2014

  87. S. Zhang, M. Chen, Z. Li and L. Huang, “Optimal Distributed Broadcasting with Per-neighbor Queues in Acyclic Overlay Networks with Arbitrary Underlay Capacity Constraints,” Proceedings of IEEE International Symposium on Information Theory (ISIT), July 2013. [ArXiv Technical Report arXiv:1301.5107v1].

  88. L. Huang, “Optimal Sleep-Wake Scheduling for Energy Harvesting Smart Mobile Devices,” Proceedings of the 11th Int. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Tsukuba Science City, Japan, May 2013. [Note: In this online version, we fixed some bugs in the orginal paper.]

  89. L. Huang and J. Walrand, “A Benes Packet Network,” Proceedings of the 32nd Annual IEEE International Conference on Computer Communications (INFOCOM), April 2013. [ArXiv Technical Report, arxiv:1208.0561v1].

  90. L. Huang, J. Walrand and K. Ramchandran, “Optimal Demand Response with Energy Storage Management,” Proceedings of IEEE International Conference on Smart Grid Communications (SmartGridComm), November 2012. [ArXiv Technical Report, arxiv:1205.4279v1].

  91. L. Huang, S. Pawar, H. Zhang, and K. Ramchandran, “Codes Can Reduce Queueing Delay in Data Centers,” Proceedings of IEEE International Symposium on Information Theory (ISIT), July 2012. [ArXiv Technical Report aXiv:1202.1359v1].

  92. L. Huang, J. Walrand, and K. Ramchandran, ‘‘Optimal Power Procurement and Demand Response with Quality-of-Usage Guarantees,’’ Proceedings of IEEE Power & Energy Society General Meeting (PESGM), July 2012. [ArXiv Technical Report, arXiv:1112.0623v1]

  93. Y. Yao, L. Huang, A. Sharma, L. Golubchik and M. J. Neely, “Data Centers Power Reduction: A two Time Scale Approach for Delay Tolerant Workloads,” Proc. of the 31st Annual IEEE International Conference on Computer Communications (INFOCOM), March 2012. (USC CS Technical Report 11-9020)

  94. A. Y. S. Lam, L. Huang, A. Silva and W. Saad, “A Multi-Layer Market for Vehicle-to-Grid Energy Trading in the Smart Grid,” Proc. of The 1st IEEE INFOCOM Workshop on Green Networking and Smart Grids (INFOCOM-GNSG), March 2012.

  95. L. Huang, J. Walrand and K. Ramchandran, “Optimal Smart Grid Tariffs,” Information Theory and Applications Workshop (ITA) (Invited), San Diego, February 2012.

  96. L. Huang and M. J. Neely, “Utlity Optimal Scheduling in Processing Networks,” IFIP Performance (Performance), Amsterdam, Oct 2011.

  97. L. Huang and M. J. Neely, “Utility Optimal Scheduling in Energy Harvesting Networks,” Proc. of Twelfth ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), Paris, May 2011.

  98. L. Huang, S. Moeller, M. J. Neely and B. Krishnamachari, “LIFO-Backpressure Achieves Near Optimal Utility-Delay Tradeoff ,” Proc.of the 9th Int. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Princeton, May 2011. [Invited for fast-track journal publication in Elsevier's Performance Evaluation (5 papers out of 40 accepted papers)]

  99. M. J. Neely and L. Huang, “Dynamic product assembly and inventory control for maximum profit,” Proc.of IEEE Conf. on Decision and Control (CDC), Atlanta, GA, Dec. 2010. A longer version is available at arXiv:1004.0479v1.

  100. L. Huang and M. J. Neely, “Delay Efficient Scheduling via Redundant Constraints in Multihop Networks,” Proc. of the 8th Int. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Avignon, June 2010. [Invited for fast-track journal publication in Elsevier's Performance Evaluation]

  101. L. Huang and M. J. Neely, “Delay Reduction via Lagrange Multipliers in Stochastic Network Optimization,” Proc. of the 7th Int. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Seoul, June 2009. Slides

  102. H. Liu, L. Huang, B. Krishnamachri and Q. Zhao, “A Negotiation Game for Multichannel Access in Cognitive Radio Networks,” The Fourth International Wireless Internet Conference (WICON) 2008, Hawaii, USA.

  103. L. Huang and M. J. Neely, “The Optimality of Two Prices: Maximizing Revenue in a Stochastic Network,” Proc. of 45th Annual Allerton Conference on Communication, Control, and Computing (invited paper), Sept. 2007. Slides

Journal Papers (published/accepted):

  1. J. Huang, L. Golubchik, L. Huang, “When Lyapunov Drift Based Queue Scheduling Meets Adversarial Bandit Learning,” IEEE/ACM Transactions on Networking (TON), to appear.

  2. P. Hu, Y. Chen, L. Pan, Z. Fang, F. Xiao, L. Huang, “Multi-User Delay-Constrained Scheduling with Deep Recurrent Reinforcement Learning,” IEEE/ACM Transactions on Networking (TON), to appear.

  3. Y. Huang, L. Huang, “A Survey of Multi-modal Learning Theory,” Acta Scientiarum Naturalium Universitatis Sunyatseni (中山大学学报(自然科学版)), 62(05):38-49, September 2023.

  4. Y. Huang, Y. Cheng, Y. Liang, L. Huang, “Online Min-max Problems: Nonconvexity and Saddle Point,” Transactions on Machine Learning Research (TMLR), July 2023.

  5. Z. Li, X. Wang, L. Pan, L. Zhu, Z. Wang, J. Feng, C. Deng, L. Huang, “Network Topology Optimization via Deep Reinforcement Learning,” IEEE Transactions on Communications (TCOM), vol. 71, issue 5, pp. 2847 - 2859, February 2023.

  6. H. Zhou, K. Lv, L. Huang, X. Ma, “Quantum Network: Security Assessment and Key Management,” IEEE/ACM Transactions on Networking (TON), vol. 30, issue 3, pp. 1328-1339, June 2022.

  7. Q. Liu, W. Wu, L. Huang, Z. Fang, “Simultaneously Achieving Sublinear Regret and Constraint Violations for Online Convex Optimization with Time-varying Constraints,” Elsevier's Performance Evaluation (PEVA), vol. 152, December 2021. [Accepted directly through IFIP Performance 2021 ]

  8. L. Pan, Q. Cai, L. Huang “Exploration in Policy Optimization through Multiple Paths,” Journal of Autonomous Agents and Multi-Agent Systems, Volume 35, Issue 2, October 2021. [Fast-track publication from AAMAS 2020].

  9. L. Huang, ‘‘Fast-Convergent Learning-aided Control in Energy Harvesting Networks,’’ IEEE Transactions on Mobile Computing (TMC), vol. 19, no. 12, pp. 2793-2803, December 2020. [arXiv Technical Report, arXiv:1503.05665]

  10. Y. Huang, L. Huang, “Heavy Traffic Analysis of Approximate Max-Weight Matching Algorithms for Input-Queued Switches,” Elsevier's Performance Evaluation (PEVA), Volume 144, December 2020. [Accepted directly through IFIP Performance 2020 ]

  11. T. Hao, J. Zhou, Y. Cheng, L. Huang, H. Wu, “A Unified Framework for User Identification across Online and Offline Data,” IEEE Transactions on Knowledge and Data Engineering (TKDE), to appear.

  12. Z. Fang, L.Huang, and A. Wierman, ‘‘Loyalty Programs in the Sharing Economy: Optimality and Competition,’’ Elsevier's Performance Evaluation (PEVA), Volume 143, November 2020. [arXiv Technical Report, arXiv:1604.01627]

  13. Z. Fang, L.Huang, and A. Wierman, ‘‘Prices and Subsidies in the Sharing Economy,’’ Elsevier's Performance Evaluation (PEVA), Volume 136, December 2019. [arXiv Technical Report, arXiv:1604.01627]

  14. K. Chen and L. Huang, “Timely-Throughput Optimal Scheduling with Prediction,” IEEE/ACM Transactions on Networking (TON), vol. 26, issue 6, pp. 2457-2470, December 2018. [arXiv Technical Report arXiv:1712.05677].

  15. L.Huang, M. Chen, and Y. Liu, ‘‘Learning-aided Stochastic Network Optimization with Imperfect State Prediction,’’ IEEE/ACM Transactions on Networking (TON), vol. 26, no. 4, pp. 1810-1820, August 2018. [arXiv Technical Report, arXiv:1705.05058]

  16. X. Wang, X. Chen, T. Chen, L. Huang, and G. Giannakis, ‘‘Two-scale Stochastic Control for Multipoint Communication Systems with Renewables,’’ IEEE Transactions on Smart Grid (TSG), vol.9, issue 3, pp. 1822-1834, May 2018.

  17. L. Huang, “Intelligence of Smart Systems: Model, Bounds and Algorithms,” IEEE/ACM Transactions on Networking (TON), vol. 25, issue. 5, pp. 2960-2973, October 2017. [ArXiv Technical Report, arXiv:1605.02585]

  18. (Tutorial/Editorial) L. Duan, L. Huang, C. Langbort, A. Pozdnukhov, J. Walrand, and L. Zhang, ‘‘Human-in-the-Loop Mobile Networks:A Survey of Recent Advancements, ”, IEEE Journal of Selected Areas in Communications - Special Issue on Human-in-the-loop Mobile Networks (JSAC), vol. 35, No. 4, April 2017.

  19. S. Supittayapornpong, L. Huang and M. J. Neely, “Time-Average Optimization with Nonconvex Decision Set and its Convergence,” IEEE Trans. on Automatic Control (TAC) (Technical Note), Vol. 62, Issue 8, 4202-4208, March 2017. [ArXiv Technical Report, arXiv:1610.02617]

  20. K. Lee, N. Shah, L. Huang, and K. Ramchandran, ‘‘The MDS Queue: Analyzing the Latency Performance of Codes,’’ IEEE Trans. on Information Theory (TIT), vol 63, issue 5, pp. 2822-2842, May 2017.

  21. S. Zhang, L. Huang, M. Chen, and X. Liu, ‘‘Proactive Serving Decreases User Delay Exponentially: The Light-tailed Service Time Case,’’ IEEE/ACM Transactions on Networking (TON), vol. 25, issue 2, 708-723, April 2017.

  22. L. Huang, “Optimal Sleep-Wake Scheduling for Energy Harvesting Smart Mobile Devices,” IEEE Transactions on Mobile Computing (TMC), vol. 16, issue 5, pp 1394-1407, May 2017.

  23. L. Huang, ‘‘The Value-of-Information in Matching with Queues,’’ IEEE/ACM Transactions on Networking (TON), vol. 25, issue 1, pp. 29-42, Feb 2017. [ArXiv Technical Report, arXiv:1503.07975v1 ]

  24. L. Huang, S. Zhang, M. Chen, and X. Liu, ‘‘When Backpressure meets Predictive Scheduling,’’ IEEE/ACM Transactions on Networking (TON), vol. 24, issue 4, pp. 2237-2250, August 2016.

  25. H. Yu, M. Cheung, L.Huang and J. Huang, “Power-Delay Tradeoff with Predictive Scheduling in Integrated Cellular and Wi-Fi Networks,” IEEE Journal of Selected Areas in Communications - Special Issue on Energy-Efficient Techniques for 5G Wireless Communication Systems (JSAC), vol. 34, issue 4, pp. 735-742, April 2016.

  26. L. Huang, ‘‘Receding Learning-aided Control in Stochastic Networks,’’ Elsevier's Performance Evaluation (PEVA), Vol. 91, pp. 150-169, September 2015. [Accepted directly through IFIP Performance 2015 ]

  27. N. Edalat, J. Walrand, M. Mehul, and L. Huang, ‘‘A Methodology for Designing the Control of Energy Harvesting Sensor Nodes,’’ IEEE Journal of Selected Areas in Communications - Special Issue on Wireless Communications Powered by Energy Harvesting and Wireless Energy Transfer (JSAC), Vol. 33, issue:3, pp. 598-607, March 2015.

  28. Y. Yao, L. Huang, A. Sharma, L. Golubchik and M. J. Neely, “Power Cost Reduction in Distributed Data Centers: A Two-Time-Scale Approach for Delay Tolerant Workloads,” IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 25, no. 1, pp. 200-211, Jan. 2014.

  29. L. Huang and M. J. Neely, “Utility Optimal Scheduling in Energy Harvesting Networks,” IEEE/ACM Transactions on Networking (TON), Volume 21, Issue 4, Pages 1117-1130, August 2013. [ArXiv Technical Report, arXiv:1012.1945v1.]

  30. L. Huang, S. Moeller, M. J. Neely and B. Krishnamachari, “LIFO-Backpressure Achieves Near Optimal Utility-Delay Tradeoff,” IEEE/ACM Transactions on Networking (TON), Volume 21, Issue 3, Pages 831-844, June 2013. [ArXiv Technical Report, arXiv:1008.4895v1.]

  31. L. Huang and M. J. Neely, “Utility Optimal Scheduling in Processing Networks,” Elsevier's Performance Evaluation (PEVA), Volume 68, Issue 11, Pages 1002–1021, November 2011. [Accepted directly through IFIP Performance 2011 ] [ArXiv Technical Report, arXiv:1010.1862v1].

  32. L. Huang and M. J. Neely, “Delay Efficient Scheduling via Redundant Constraints in Multihop Networks,” Elsevier's Performance Evaluation (PEVA), Volume 68, Issue 8, August 2011, Pages 670-689. [Invited for fast-track journal publication]

  33. L. Huang and M. J. Neely, “Delay Reduction via Lagrange Multipliers in Stochastic Network Optimization,” IEEE Trans. on Automatic Control (TAC), Volume 56, Issue 4, pp. 842-857, April 2011. [The IEEE version can be found here. A longer version is available at arXiv:0904.3795v1]

  34. L. Huang and M. J. Neely, “The Optimality of Two Prices: Maximizing Revenue in a Stochastic Communication System,” IEEE/ACM Transactions on Networking (TON), Vol. 18, No.2, April 2010. [The IEEE version can be found here]