Algorithm

HyperAgent - A Simple, Efficient, Scalable and Provable RL Framework

Practically and provably efficient RL under resource constraints!

Mar 23, 2024 1:30 PM Rice University

Yingru LI

Optimistic Thompson Sampling for No-Regret Learning in Unknown Games

Game-theoretic decision-making in multi-agent systems. I developed optimistic TS type algorithm that significantly reduce experimental costs in applications such as traffic management and radar communications.

Yingru Li, Liangqi Liu, Wenqiang Pu, Hao Liang, Zhi-Quan Luo

HyperAgent - A Simple, Efficient and Scalable RL Framework for Complex Environments

Practically and provably efficient RL under resource constraints!

Jan 13, 2024 1:20 PM Daoyuan Building

Yingru LI

HyperAgent - A Simple, Efficient and Scalable RL Framework for Complex Environments

Towards AGI for Humanity through Efficient Reinforcement Learning

Addressing efficiency chanllenge in RL by HyperFQI algorithm

Oct 21, 2023 2:30 PM Teaching B Building

Yingru LI

Towards AGI for Humanity through Efficient Reinforcement Learning

No-Regret Learning in Unknown Game with Applications

Aug 23, 2022 2:00 PM

Yingru LI

No-Regret Learning in Unknown Game with Applications

HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning

TL;DR: We design a practical randomized exploration method to address the sample efficiency issue in online reinforcement learning.

Ziniu Li, Yingru Li* (corresponding), Yushun Zhang, Tong Zhang, Zhi-Quan Luo

HyperDQN - Randomized Exploration for Deep Reinforcement Learning

Dec 14, 2021 12:00 AM NeurIPS 2021

Yingru LI

HyperDQN - Randomized Exploration for Deep Reinforcement Learning

Hidden community detection in social networks

Kun He, Yingru Li* (corresponding), Sucheta Soundarajan, John E Hopcroft