no code implementations • 22 Mar 2024 • Zuyuan Zhang, Hanhan Zhou, Mahdi Imani, Taeyoung Lee, Tian Lan
With the advancements of artificial intelligence (AI), we're seeing more scenarios that require AI to work closely with other agents, whose goals and strategies might not be known beforehand.
no code implementations • 12 Dec 2023 • Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Gina Adam, Nathaniel D. Bastian, Tian Lan
Many cybersecurity problems that require real-time decision-making based on temporal observations can be abstracted as a sequence modeling problem, e. g., network intrusion detection from a sequence of arriving packets.
no code implementations • 28 Aug 2023 • Hanhan Zhou, Tian Lan, Vaneet Aggarwal
Offline reinforcement learning aims to utilize datasets of previously gathered environment-action interaction records to learn a policy without access to the real environment.
1 code implementation • 21 Feb 2023 • Yongsheng Mei, Hanhan Zhou, Tian Lan, Guru Venkataramani, Peng Wei
To this end, we propose MAC-PO, which formulates optimal prioritized experience replay for multi-agent problems as a regret minimization over the sampling weights of transitions.
no code implementations • 11 Feb 2023 • Yongsheng Mei, Hanhan Zhou, Tian Lan
Such an optimization problem can be relaxed and solved using the Lagrangian multiplier method to obtain the close-form optimal projection weights.
1 code implementation • 22 Jun 2022 • Hanhan Zhou, Tian Lan, Vaneet Aggarwal
Multi-agent reinforcement learning (MARL) has witnessed significant progress with the development of value function factorization methods.
1 code implementation • 27 Jan 2022 • Hanhan Zhou, Tian Lan, Guru Venkataramani, Wenbo Ding
In this paper, we present a unifying framework for heterogeneous FL algorithms with {\em arbitrary} adaptive online model pruning and provide a general convergence analysis.
1 code implementation • 4 Jan 2022 • Hanhan Zhou, Tian Lan, Vaneet Aggarwal
To this end, we present LSF-SAC, a novel framework that features a variational inference-based information-sharing mechanism as extra state information to assist individual agents in the value function factorization.
no code implementations • 23 Nov 2021 • Hanhan Zhou, Tian Lan, Guru Venkataramani
The virtual try-on system has gained great attention due to its potential to give customers a realistic, personalized product presentation in virtualized settings.