Multi-Labelled Value Networks for Computer Go. - Ti-Rong Wu; I-Chen Wu; Guan-Wun Chen; Ting-Han Wei; Tung-Yi Lai; Hung-Chun Wu; Li-Cheng Lan (CoRR, 2017)

Multilabeled Value Networks for Computer Go. - Ti-Rong Wu; I-Chen Wu; Guan-Wun Chen; Ting-Han Wei; Hung-Chun Wu; Tung-Yi Lai; Li-Cheng Lan (IEEE Trans. Games, 2018)

Multiple Policy Value Monte Carlo Tree Search. - Li-Cheng Lan; Wei Li; Ting-Han Wei; I-Chen Wu (IJCAI, 2019)

How much progress have we made in neural network training? A New Evaluation Protocol for Benchmarking Optimizers. - Yuanhao Xiong; Xuanqing Liu; Li-Cheng Lan; Yang You 001; Si Si; Cho-Jui Hsieh (CoRR, 2020)

Learning to Stop: Dynamic Simulation Monte-Carlo Tree Search. - Li-Cheng Lan; Meng-Yu Tsai 001; Ti-Rong Wu; I-Chen Wu; Cho-Jui Hsieh (CoRR, 2020)

Learning to Stop: Dynamic Simulation Monte-Carlo Tree Search. - Li-Cheng Lan; Ti-Rong Wu; I-Chen Wu; Cho-Jui Hsieh (AAAI, 2021)

Learning to Schedule Learning rate with Graph Neural Networks. - Yuanhao Xiong; Li-Cheng Lan; Xiangning Chen; Ruochen Wang; Cho-Jui Hsieh (ICLR, 2022)

Are AlphaZero-like Agents Robust to Adversarial Perturbations? - Li-Cheng Lan; Huan Zhang 001; Ti-Rong Wu; Meng-Yu Tsai 001; I-Chen Wu; Cho-Jui Hsieh (NeurIPS, 2022)

Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories. - Li-Cheng Lan; Huan Zhang 001; Cho-Jui Hsieh (ICLR, 2023)

Expert Proximity as Surrogate Rewards for Single Demonstration Imitation Learning. - Chia-Cheng Chiang; Li-Cheng Lan; Wei-Fang Sun; Chien Feng; Cho-Jui Hsieh; Chun-Yi Lee (ICML, 2024)

Exploring Expert Failures Improves LLM Agent Tuning. - Li-Cheng Lan; Andrew Bai; Minhao Cheng; Cho-Jui Hsieh; Tianyi Zhou 001 (CoRR, 2025)