Toward A High-Performance Emulation Platformfor Brain-Inspired Intelligent SystemsExploring Dataflow-Based Execution Model and Beyond. - Sihan Zeng; Jose Manuel Monsalve Diaz; Siddhisanket Raskar (COMPSAC (2), 2019)

Fast Compressive Sensing Recovery Using Generative Models with Structured Latent Variables. - Shaojie Xu; Sihan Zeng; Justin Romberg (ICASSP, 2019)

Modeling Spatio-Temporal App Usage for a Large User Population. - Huandong Wang; Yong Li 008; Sihan Zeng; Gang Wang 011; Pengyu Zhang; Pan Hui 001; Depeng Jin (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2019)

An approach for medical event detection in Chinese clinical notes of electronic health records. - Xuesi Zhou; Haoqi Xiong; Sihan Zeng; Xiangling Fu; Ji Wu 002 (BMC Medical Informatics Decis. Mak., 2019)

H-DrunkWalk: Collaborative and Adaptive Navigation for Heterogeneous MAV Swarm. - Xinlei Chen; Carlos Ruiz Dominguez; Sihan Zeng; Liyao Gao; Aveek Purohit; Stefano Carpin; Pei Zhang 001 (ACM Trans. Sens. Networks, 2020)

Human Mobility Prediction Using Sparse Trajectory Data. - Huandong Wang; Sihan Zeng; Yong Li 008; Pengyu Zhang; Depeng Jin (IEEE Trans. Veh. Technol., 2020)

Finite-Time Analysis of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning. - Sihan Zeng; Thinh T. Doan 001; Justin Romberg (CDC, 2021)

A decentralized policy gradient approach to multi-task reinforcement learning. - Sihan Zeng; Malik Aqeel Anwar; Thinh T. Doan 001; Arijit Raychowdhury; Justin Romberg (UAI, 2021)

A Reinforcement Learning Approach to Parameter Selection for Distributed Optimization in Power Systems. - Sihan Zeng; Alyssa Kody; Youngdae Kim; Kibaek Kim; Daniel K. Molzahn (CoRR, 2021)

Predictability and Prediction of Human Mobility Based on Application-Collected Location Data. - Huandong Wang; Sihan Zeng; Yong Li 008; Depeng Jin (IEEE Trans. Mob. Comput., 2021)

Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes. - Sihan Zeng; Thinh T. Doan 001; Justin Romberg (CDC, 2022)

Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games. - Sihan Zeng; Thinh T. Doan 001; Justin Romberg (NeurIPS, 2022)

An unsupervised font style transfer model based on generative adversarial networks. - Sihan Zeng; Zhongliang Pan (Multim. Tools Appl., 2022)

Sequential Fair Resource Allocation under a Markov Decision Process Framework. - Parisa Hassanzadeh; Eleonora Kreacic; Sihan Zeng; Yuchen Xiao; Sumitra Ganesh (ICAIF, 2023)

Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems. - Sihan Zeng; Thinh T. Doan 001; Justin Romberg (NeurIPS, 2023)

InkGAN: Generative Adversarial Networks for Ink-And-Wash Style Transfer of Photographs. - Keyi Yu; Yu Wang; Sihan Zeng; Chen Liang; Xiaoyu Bai; Dachi Chen; Wenping Wang (Adv. Artif. Intell. Mach. Learn., 2023)

Near-Optimal Fair Resource Allocation for Strategic Agents without Money: A Data-Driven Approach. - Sihan Zeng; Sujay Bhatt; Eleonora Kreacic; Parisa Hassanzadeh; Alec Koppel; Sumitra Ganesh (CoRR, 2023)

Designing policy optimization algorithms for multi-agent reinforcement learning. - Sihan Zeng (2023)

Finite-Time Convergence Rates of Decentralized Stochastic Approximation With Applications in Multi-Agent and Multi-Task Learning. - Sihan Zeng; Thinh T. Doan 001; Justin Romberg (IEEE Trans. Autom. Control., 2023)

Fast two-time-scale stochastic gradient method with applications in reinforcement learning. - Sihan Zeng; Thinh T. Doan 001 (COLT, 2024)

QCQP-Net: Reliably learning feasible alternating current optimal power flow solutions under constraints. - Sihan Zeng; Youngdae Kim; Yuxuan Ren; Kibaek Kim (L4DC, 2024)

Learning Payment-Free Resource Allocation Mechanisms. - Sihan Zeng; Sujay Bhatt; Eleonora Kreacic; Parisa Hassanzadeh; Alec Koppel; Sumitra Ganesh (WSC, 2024)

Natural Policy Gradient and Actor Critic Methods for Constrained Multi-Task Reinforcement Learning. - Sihan Zeng; Thinh T. Doan 001; Justin Romberg (CoRR, 2024)

Regularized Proportional Fairness Mechanism for Resource Allocation Without Money. - Sihan Zeng; Sujay Bhatt; Alec Koppel; Sumitra Ganesh (Trans. Mach. Learn. Res., 2024)

A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning. - Sihan Zeng; Thinh T. Doan 001; Justin Romberg (SIAM J. Optim., 2024)

Approximate Equivariance in Reinforcement Learning. - Jung Yeon Park; Sujay Bhatt; Sihan Zeng; Lawson L. S. Wong; Alec Koppel; Sumitra Ganesh; Robin Walters 001 (AISTATS, 2025)

Learning in Herding Mean Field Games: Single-Loop Algorithm with Finite-Time Convergence Analysis. - Sihan Zeng; Sujay Bhatt; Alec Koppel; Sumitra Ganesh (AISTATS, 2025)

Partially Observable Contextual Bandits With Linear Payoffs. - Sihan Zeng; Sujay Bhatt; Alec Koppel; Sumitra Ganesh (ICASSP, 2025)

ADAGE: A Generic Two-layer Framework for Adaptive Agent based Modelling. - Benjamin Patrick Evans; Sihan Zeng; Sumitra Ganesh; Leo Ardon (AAMAS, 2025)

Stackelberg Game-Based Task Offloading for Joint Service Caching and Resource Allocation Optimization in UAV-Assisted VEC. - Chunlin Li 001; Long Yu; Sihan Zeng; Yong Zhang 057; Kun Jiang; Shaohua Wan 001 (ACM Trans. Internet Things, 2025)

Nonasymptotic CLT and Error Bounds for Two-Time-Scale Stochastic Approximation. - Seo Taek Kong; Sihan Zeng; Thinh T. Doan 001; R. Srikant 001 (CoRR, 2025)

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation. - Mingfu Liang; Xi Liu; Rong Jin 001; Boyang Liu; Qiuling Suo; Qinghai Zhou; Song Zhou; Laming Chen; Hua Zheng; Zhiyuan Li; Shali Jiang 003; Jiyan Yang; et al. (CoRR, 2025)

Accelerating Multi-Task Temporal Difference Learning under Low-Rank Representation. - Yitao Bai; Sihan Zeng; Justin Romberg; Thinh T. Doan 001 (CoRR, 2025)

Generating Structured Plan Representation of Procedures with LLMs. - Deepeka Garg; Sihan Zeng; Sumitra Ganesh; Leo Ardon (CoRR, 2025)