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ORCIDBhargav Ganguly
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2020 – today
- 2025
[c5]Bhargav Ganguly, Yang Xu, Vaneet Aggarwal:
Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes. ICML 2025- 2024
- [j3]Jiayu Chen, Bhargav Ganguly, Yang Xu, Yongsheng Mei, Tian Lan, Vaneet Aggarwal:
Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions. Trans. Mach. Learn. Res. 2024 (2024) - [j2]Bhargav Ganguly
, Vaneet Aggarwal:
Online Federated Learning via Non-Stationary Detection and Adaptation Amidst Concept Drift. IEEE/ACM Trans. Netw. 32(1): 643-653 (2024) - [i7]Jiayu Chen, Bhargav Ganguly, Yang Xu, Yongsheng Mei, Tian Lan, Vaneet Aggarwal:
Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions. CoRR abs/2402.13777 (2024) - [i6]Jiayu Chen, Bhargav Ganguly, Tian Lan, Vaneet Aggarwal:
Variational Offline Multi-agent Skill Discovery. CoRR abs/2405.16386 (2024) - 2023
- [j1]Bhargav Ganguly, Seyyedali Hosseinalipour, Kwang Taik Kim, Christopher G. Brinton, Vaneet Aggarwal, David J. Love, Mung Chiang:
Multi-Edge Server-Assisted Dynamic Federated Learning With an Optimized Floating Aggregation Point. IEEE/ACM Trans. Netw. 31(6): 2682-2697 (2023) - [c4]Jiayu Chen, Bhargav Ganguly, Sameeran G. Kanade, Vincent G. Duffy:
Impact of AI on Mobile Computing: A Systematic Review from a Human Factors Perspective. HCI (53) 2023: 24-38 - [i5]Bhargav Ganguly, Yulian Wu, Di Wang, Vaneet Aggarwal:
Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning. CoRR abs/2302.08617 (2023) - [i4]Bhargav Ganguly, Vaneet Aggarwal:
Quantum Acceleration of Infinite Horizon Average-Reward Reinforcement Learning. CoRR abs/2310.11684 (2023) - 2022
- [c3]Alec Koppel, Amrit Singh Bedi, Bhargav Ganguly, Vaneet Aggarwal:
Convergence Rates of Average-Reward Multi-agent Reinforcement Learning via Randomized Linear Programming. CDC 2022: 4545-4552 - [i3]Bhargav Ganguly, Seyyedali Hosseinalipour, Kwang Taik Kim, Christopher G. Brinton, Vaneet Aggarwal, David J. Love, Mung Chiang:
Multi-Edge Server-Assisted Dynamic Federated Learning with an Optimized Floating Aggregation Point. CoRR abs/2203.13950 (2022) - [i2]Bhargav Ganguly, Vaneet Aggarwal:
Online Federated Learning via Non-Stationary Detection and Adaptation amidst Concept Drift. CoRR abs/2211.12578 (2022) - 2021
- [c2]Alec Koppel, Amrit Singh Bedi, Bhargav Ganguly, Vaneet Aggarwal:
Randomized Linear Programming for Tabular Average-Cost Multi-agent Reinforcement Learning. ACSCC 2021: 1023-1026 - [c1]Mridul Agarwal, Bhargav Ganguly, Vaneet Aggarwal:
Communication efficient parallel reinforcement learning. UAI 2021: 247-256 - [i1]Mridul Agarwal, Bhargav Ganguly, Vaneet Aggarwal:
Communication Efficient Parallel Reinforcement Learning. CoRR abs/2102.10740 (2021)
Coauthor Index
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