Publications
Representative/Recent Works
Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems
T. Chen, Y. Sun and W. Yin
Proc. of Neural Information Processing Systems (NeurIPS), Virtual, December 6-14, 2021. (Spotlight)
Is Bayesian Model-Agnostic Meta Learning Better than Model-Agnostic Meta Learning, Provably?
L. Chen and T. Chen
Proc. of Intl. Conf. on Artificial Intelligence and Statistics (AISTATS), Virtual, March 28 - 30, 2022.
Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization
T. Chen, Y. Sun and W. Yin
IEEE Transactions on Signal Processing, vol. 69, pp. 4937-4948, June 2021.
The conference version has received the 2021 ICASSP Best Student Paper Award.
Catastrophic Data Leakage in Vertical Federated Learning
X. Jin, P.-Y. Chen, C.-Y. Hsu, C.-M. Yu, and T. Chen
Proc. of Neural Information Processing Systems (NeurIPS), Virtual, December 6-14, 2021.
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning [Talk], [Poster], and [Code]
T. Chen, G. B. Giannakis, T. Sun and W. Yin
Proc. of Neural Information Processing Systems (NeurIPS), Montreal, Canada, December 3-8, 2018. (Spotlight)
An Online Convex Optimization Approach to Proactive Network Resource Allocation
T. Chen, Q. Ling and G. B. Giannakis
IEEE Transactions on Signal Processing, vol. 65, no. 24, pp. 6350-6364, December 2017.
Recent Submissions
Dissertation
Journal papers
Adaptive Temporal Difference Learning with Linear Function Approximation
T. Sun, H. Shen, T. Chen and D. Li
IEEE Transactions on Pattern Analysis and Machine Intelligence, to appear, 2021.
LASG: Lazily Aggregated Stochastic Gradients for Communication-Efficient Distributed Learning
T. Chen, Y. Sun and W. Yin
IEEE Transactions on Signal Processing, vol. 69, pp. 4637 - 4651, July 2021.
Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization
T. Chen, Y. Sun and W. Yin
IEEE Transactions on Signal Processing, vol. 69, pp. 4937 - 4948, June 2021.
Byzantine-Resilient Decentralized TD Learning with Linear Function Approximation.
Z. Wu, H. Shen, T. Chen, and Q. Ling
IEEE Transactions on Signal Processing, vol. 69, pp. 3839 - 3853, June 2021.
Communication-Efficient Policy Gradient Methods for Distributed Reinforcement Learning
T. Chen, K. Zhang, G. B. Giannakis, and T. Başar
IEEE Transactions on Control of Network Systems, to appear, 2021.
Lazily Aggregated Quantized Gradient Innovation for Communication-Efficient Federated Learning
J. Sun, T. Chen and G. B. Giannakis, Z. Yang
IEEE Transactions on Pattern Analysis and Machine Intelligence, to appear, 2021.
Federated Variance-Reduced Stochastic Gradient Descent with Robustness to Byzantine Attacks
Z. Wu, Q. Ling, T. Chen and G. B. Giannakis
IEEE Transactions on Signal Processing, vol. 68, pp. 4583-4596, December 2020.
Secure Mobile Edge Computing in IoT via Collaborative Online Learning
B. Li, T. Chen and G. B. Giannakis
IEEE Transactions on Signal Processing, vol. 67, no. 23, pp. 5922-5935, December 2019.
Learning and Management for Internet-of-Things: Accounting for Adaptivity and Scalability
T. Chen, S. Barbarossa, X. Wang, G. B. Giannakis and Z.-L. Zhang
Proceedings of the IEEE, vol. 107, no. 4, pp. 778-796, April 2019.
Random Feature-based Online Multi-kernel Learning in Environments with Unknown Dynamics
Y. Shen, T. Chen and G. B. Giannakis
Journal of Machine Learning Research, vol. 20, no. 22, pp. 1-36, February 2019.
Real-time Optimal Energy Management with Reduced Battery Capacity Requirements
B. Li, T. Chen, X. Wang and G. B. Giannakis
IEEE Transactions on Smart Grid, vol. 10, no. 2, pp. 1928-1938, March 2019.
Bandit Convex Optimization for Scalable and Dynamic IoT Management
T. Chen and G. B. Giannakis
IEEE Internet of Things Journal, vol. 6, no. 1, pp. 1276-1286, February 2019.
Heterogeneous Online Learning for "Thing-Adaptive'' Fog Computing in IoT
T. Chen, Q. Ling, Y. Shen and G. B. Giannakis
IEEE Internet of Things Journal, vol. 5 , no. 6 , pp. 4328 - 4341, December 2018.
Learn-and-Adapt Stochastic Dual Gradients for Network Resource Allocation
T. Chen, Q. Ling and G. B. Giannakis
IEEE Transactions on Control of Network Systems, vol. 5, no. 4, pp. 1941-1951, December 2018.
Two-Scale Stochastic Control for Multipoint Communication Systems with Renewables
X. Wang, X. Chen, T. Chen, L. Huang and G. B. Giannakis
IEEE Transactions on Smart Grid, vol. 9, no. 3, pp. 1822 - 1834, May. 2018.
An Online Convex Optimization Approach to Proactive Network Resource Allocation
T. Chen, Q. Ling and G. B. Giannakis
IEEE Transactions on Signal Processing, vol. 65, no. 24, pp. 6350-6364, Dec. 2017.
Real-time Energy Trading and Future Planning for Fifth-Generation Wireless Communications
X. Chen, W. Ni, T. Chen, I. Collins, X. Wang and G. B. Giannakis
IEEE Wireless Communications Magazine, vol.24, no. 4, pp. 24-30, Aug. 2017.
Stochastic Averaging for Constrained Optimization with Application to Online Resource Allocation
T. Chen, A. Mokhtari, X. Wang, A. Ribeiro and G. B. Giannakis
IEEE Transactions on Signal Processing, vol. 65, no. 12, pp. 3078-3093, Jun. 2017.
Dynamic Resource Allocation for Smart-Grid Powered MIMO Downlink Transmissions
X. Wang, T. Chen, X. Chen, X. Zhou and G. B. Giannakis
IEEE Journal on Selected Areas in Communications, Vol. 34, No. 12, pp. 3354 - 3365, Dec. 2016.
Dynamic Energy Management for Smart-Grid-Powered Coordinated Multipoint Systems
X. Wang, Y. Zhang, T. Chen and G. B. Giannakis
IEEE Journal on Selected Areas in Communications, vol. 65, no. 12, pp. 3078-3093, Jun. 2016.
Robust Workload and Energy Management for Sustainable Data Centers
T. Chen, Y. Zhang X. Wang, and G. B. Giannakis
IEEE Journal on Selected Areas in Communications, Vol. 34, No. 3, pp. 651-664, Mar. 2016.
Cooling-Aware Energy and Workload Management in Data Centers via Stochastic Optimization
T. Chen, X. Wang and G. B. Giannakis
IEEE Journal on Special Topics in Signal Processing, Vol. 10, No. 2, pp. 402-415, Mar. 2016.
Energy-Efficient Transmission Schedule for Delay-Limited Bursty Data Arrivals under Non-Ideal Circuit Power Consumption
Z. Nan, T. Chen, X. Wang and W. Ni
IEEE Transaction on Vehicular Technology, Vol. 65, No. 8, pp. 6588 - 6600, Aug. 2016.
Optimal Scheduling for Wireless On-Demand Data Packet Delivery to High-Speed Trains
T. Chen, H. Shan and X. Wang
IEEE Transaction on Vehicular Technology, Vol. 64, No. 9, pp. 4101 - 4112, Sept. 2015.
Optimal MIMO Broadcasting for Energy Harvesting Transmitter with Non-ideal Circuit Power Consumption
X. Wang, Z. Nan and T. Chen
IEEE Transaction on Wireless Communication, Vol. 14, No. 5, pp. 2500 - 2512, May 2015.
Selected Conference papers (not updated)
Federated Multi-armed Bandit via Uncoordinated Exploration
Z. Yan, Q. Xiao, T. Chen and A. Tajer
Proc. of Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Virtual, May 22-27, 2022.
Is Bayesian Model-Agnostic Meta Learning Better than Model-Agnostic Meta Learning, Provably?
L. Chen and T. Chen
Proc. of Intl. Conf. on Artificial Intelligence and Statistics (AISTATS), Virtual, March 28 - 30, 2022.
A Single-Timescale Method for Stochastic Bilevel Optimization (Oral)
T. Chen, Y. Sun, Q. Xiao and W. Yin
Proc. of Intl. Conf. on Artificial Intelligence and Statistics (AISTATS), Virtual, March 28 - 30, 2022.
Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems (Spotlight)
T. Chen, Y. Sun and W. Yin
Proc. of Neural Information Processing Systems (NeurIPS), Virtual, December 6-14, 2021.
Catastrophic Data Leakage in Vertical Federated Learning
X. Jin, P.-Y. Chen, C.-Y. Hsu, C.-M. Yu, and T. Chen
Proc. of Neural Information Processing Systems (NeurIPS), Virtual, December 6-14, 2021.
A Stochastic Compositional Optimization Method with Applications to Meta
Learning (Best Student Paper)
Y. Sun, T. Chen, and W. Yin
Proc. of Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Virtual, June 6-11, 2021.
CADA: Communication-Adaptive Distributed Adam
T. Chen, Z. Guo, Y. Sun, and W. Yin
Proc. of Intl. Conf. on Artificial Intelligence and Statistics (AISTATS), Virtual, April 16-18, 2021.
Decentralized policy gradient descent ascent for safe
multi-agent reinforcement learning
S. Lu, K. Zhang, T. Chen, T. Başar, and L. Horesh,
Proc. of the Assoc. for the Advanc. of Artificial Intelligence (AAAI), Virtual, February 2-9, 2021.
Hybrid Federated Learning: Algorithms and Implementation (Best Student Paper)
- X. Zhang, W. Yin, M. Hong, and T. Chen
Proc. of NeurIPS Workshop on Scalability, Privacy, and Security in Federated Learning, Virtual, December 12, 2020.
VAFL: a Method of Vertical Asynchronous Federated Learning
T. Chen, X. Jin, Y. Sun and W. Yin
Proc. of ICML Workshop on Federated Learning for User Privacy and Data Confidentiality, Virtual, July 17-18, 2020.
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients
J. Sun*, T. Chen*, G. B. Giannakis, and Z. Yang (*equal contribution)
Proc. of Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 8-14, 2019.
Bandit Online Learning with Unknown Delays
B. Li, T. Chen, and G. B. Giannakis
Proc. of Intl. Conf. on Artificial Intelligence and Statistics (AISTATS), Naha, Japan, April 16-18, 2019.
RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets
L. Li, W. Xu, T. Chen, G. B. Giannakis, and Q. Ling
Proc. of the Assoc. for the Advanc. of Artificial Intelligence (AAAI), Honolulu, Hawai, January 27-February 1, 2019.
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning
T. Chen, G. B. Giannakis, T. Sun and W. Yin
Proc. of Neural Information Processing Systems (NeurIPS), Montreal, Canada, December 3-8, 2018.
Spotlight talk, Poster, and Matlab code.
Online Ensemble Multi-kernel Learning Adaptive to Non-stationary and Adversarial Environments
Y. Shen*, T. Chen* and G. B. Giannakis
Proc. of Intl. Conf. on Artificial Intelligence and Statistics (AISTATS), Lanzarote, Canary Islands, April 9-11, 2018.
Aggregating Flexibility of Heterogeneous Energy Resources in Distribution Networks
T. Chen, N. Li and G. B. Giannakis
Proc. of American Control Conference (ACC), Milwaukee, WI, June 27-29, 2018.
Harnessing Bandit Online Learning for Low-Latency Fog Computing in IoT
T. Chen and G. B. Giannakis
Proc. of Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Canada, April 15-20, 2018.
Online Learning for `Thing-Adaptive' Fog Computing in IoT (Best Student Paper Finalist)
T. Chen, Y. Shen, Q. Ling and G. B. Giannakis
Proc. of Asilomar Conference, Pacific Grove, CA, Oct. 29 - Nov. 1, 2017.
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