Randomized Linear Programming for Tabular Average-Cost Multi-agent Reinforcement Learning. - Alec Koppel; Amrit Singh Bedi; Bhargav Ganguly; Vaneet Aggarwal (ACSCC, 2021)

Communication efficient parallel reinforcement learning. - Mridul Agarwal; Bhargav Ganguly; Vaneet Aggarwal (UAI, 2021)

Convergence Rates of Average-Reward Multi-agent Reinforcement Learning via Randomized Linear Programming. - Alec Koppel; Amrit Singh Bedi; Bhargav Ganguly; Vaneet Aggarwal (CDC, 2022)

Impact of AI on Mobile Computing: A Systematic Review from a Human Factors Perspective. - Jiayu Chen; Bhargav Ganguly; Sameeran G. Kanade; Vincent G. Duffy (HCI (53), 2023)

Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning. - Bhargav Ganguly; Yulian Wu; Di Wang 015; Vaneet Aggarwal (CoRR, 2023)

Quantum Acceleration of Infinite Horizon Average-Reward Reinforcement Learning. - Bhargav Ganguly; Vaneet Aggarwal (CoRR, 2023)

Multi-Edge Server-Assisted Dynamic Federated Learning With an Optimized Floating Aggregation Point. - Bhargav Ganguly; Seyyedali Hosseinalipour; Kwang Taik Kim; Christopher G. Brinton; Vaneet Aggarwal; David J. Love; Mung Chiang (IEEE/ACM Trans. Netw., 2023)

Variational Offline Multi-agent Skill Discovery. - Jiayu Chen; Bhargav Ganguly; Tian Lan 001; Vaneet Aggarwal (CoRR, 2024)

Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions. - Jiayu Chen; Bhargav Ganguly; Yang Xu 003; Yongsheng Mei; Tian Lan 001; Vaneet Aggarwal (Trans. Mach. Learn. Res., 2024)

Online Federated Learning via Non-Stationary Detection and Adaptation Amidst Concept Drift. - Bhargav Ganguly; Vaneet Aggarwal (IEEE/ACM Trans. Netw., 2024)