Factorial Kernel Dynamic Policy Programming for Vinyl Acetate Monomer Plant Model Control. - Yunduan Cui; Lingwei Zhu; Morihiro Fujisaki; Hiroaki Kanokogi; Takamitsu Matsubara (CASE, 2018)

Dynamic Actor-Advisor Programming for Scalable Safe Reinforcement Learning. - Lingwei Zhu; Yunduan Cui; Takamitsu Matsubara (ICRA, 2020)

Ensuring Monotonic Policy Improvement in Entropy-regularized Value-based Reinforcement Learning. - Lingwei Zhu; Takamitsu Matsubara (CoRR, 2020)

Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning. - Toshinori Kitamura; Lingwei Zhu; Takamitsu Matsubara (ACML, 2021)

Cautious Actor-Critic. - Lingwei Zhu; Toshinori Kitamura; Takamitsu Matsubara (ACML, 2021)

Cautious Policy Programming: Exploiting KL Regularization in Monotonic Policy Improvement for Reinforcement Learning. - Lingwei Zhu; Toshinori Kitamura; Takamitsu Matsubara (CoRR, 2021)

Hierarchical Categorical Generative Modeling for Multi-omics Cancer Subtyping. - Ziwei Yang 002; Lingwei Zhu; Chen Li 027; Zheng Chen 012; Naoki Ono; Md. Altaf-Ul-Amin; Shigehiko Kanaya (BIBM, 2022)

Cancer Subtyping via Embedded Unsupervised Learning on Transcriptomics Data. - Ziwei Yang 002; Lingwei Zhu; Zheng Chen 012; Ming Huang 002; Naoaki Ono; Md. Altaf-Ul-Amin; Shigehiko Kanaya (EMBC, 2022)

Adaptive Spike-Like Representation of EEG Signals for Sleep Stages Scoring. - Lingwei Zhu; Ziwei Yang 002; Koki Odani; Guang Shi; Yirong Kan; Zheng Chen 012; Renyuan Zhang (EMBC, 2022)

Multi-Tier Platform for Cognizing Massive Electroencephalogram. - Zheng Chen 012; Lingwei Zhu; Ziwei Yang 002; Renyuan Zhang (IJCAI, 2022)

Automated Cancer Subtyping via Vector Quantization Mutual Information Maximization. - Zheng Chen 012; Lingwei Zhu; Ziwei Yang 002; Takashi Matsubara 001 (ECML/PKDD (1), 2022)

Alleviating parameter-tuning burden in reinforcement learning for large-scale process control. - Lingwei Zhu; Go Takami; Mizuo Kawahara; Hiroaki Kanokogi; Takamitsu Matsubara (Comput. Chem. Eng., 2022)

q-Munchausen Reinforcement Learning. - Lingwei Zhu; Zheng Chen 012; Eiji Uchibe; Takamitsu Matsubara (CoRR, 2022)

Enforcing KL Regularization in General Tsallis Entropy Reinforcement Learning via Advantage Learning. - Lingwei Zhu; Zheng Chen 012; Eiji Uchibe; Takamitsu Matsubara (CoRR, 2022)

Cancer Subtyping by Improved Transcriptomic Features Using Vector Quantized Variational Autoencoder. - Zheng Chen 012; Ziwei Yang 002; Lingwei Zhu; Guang Shi; Kun Yue; Takashi Matsubara 001; Shigehiko Kanaya; Md. Altaf-Ul-Amin (CoRR, 2022)

Drugs Resistance Analysis from Scarce Health Records via Multi-task Graph Representation. - Honglin Shu; Pei Gao; Lingwei Zhu; Zheng Chen 012; Yasuko Matsubara; Yasushi Sakurai (ADMA (3), 2023)

General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence. - Lingwei Zhu; Zheng Chen 012; Matthew Schlegel; Martha White (NeurIPS, 2023)

A Two-View EEG Representation for Brain Cognition by Composite Temporal-Spatial Contrastive Learning. - Zheng Chen 012; Lingwei Zhu; Haohui Jia; Takashi Matsubara 001 (SDM, 2023)

Generalized Munchausen Reinforcement Learning using Tsallis KL Divergence. - Lingwei Zhu; Zheng Chen 012; Takamitsu Matsubara; Martha White (CoRR, 2023)

Drugs Resistance Analysis from Scarce Health Records via Multi-task Graph Representation. - Honglin Shu; Pei Gao; Lingwei Zhu; Zheng Chen 012 (CoRR, 2023)

Cyclic policy distillation: Sample-efficient sim-to-real reinforcement learning with domain randomization. - Yuki Kadokawa; Lingwei Zhu; Yoshihisa Tsurumine; Takamitsu Matsubara (Robotics Auton. Syst., 2023)

Learning vector quantized representation for cancer subtypes identification. - Zheng Chen 012; Ziwei Yang 002; Lingwei Zhu; Peng Gao; Takashi Matsubara 001; Shigehiko Kanaya; Md. Altaf-Ul-Amin (Comput. Methods Programs Biomed., 2023)

Cautious policy programming: exploiting KL regularization for monotonic policy improvement in reinforcement learning. - Lingwei Zhu; Takamitsu Matsubara (Mach. Learn., 2023)

q-exponential family for policy optimization. - Lingwei Zhu; Haseeb Shah; Han Wang; Martha White (CoRR, 2024)

BEHRNOULLI: A Binary EHR Data-Oriented Medication Recommendation System. - Xihao Piao; Pei Gao; Zheng Chen 012; Lingwei Zhu; Yasuko Matsubara; Yasushi Sakurai (CoRR, 2024)

Offline Reinforcement Learning via Tsallis Regularization. - Lingwei Zhu; Matthew Schlegel; Han Wang; Martha White (Trans. Mach. Learn. Res., 2024)

q-exponential family for policy optimization. - Lingwei Zhu; Haseeb Shah; Han Wang; Yukie Nagai; Martha White (ICLR, 2025)

Fat-to-Thin Policy Optimization: Offline Reinforcement Learning with Sparse Policies. - Lingwei Zhu; Han Wang; Yukie Nagai (ICLR, 2025)

Fat-to-Thin Policy Optimization: Offline RL with Sparse Policies. - Lingwei Zhu; Han Wang; Yukie Nagai (CoRR, 2025)

Towards Physiologically Sensible Predictions via the Rule-based Reinforcement Learning Layer. - Lingwei Zhu; Zheng Chen 012; Yukie Nagai; Jimeng Sun 001 (CoRR, 2025)

A Survey of Reinforcement Learning for Software Engineering. - Dong Wang 044; Hanmo You; Lingwei Zhu; Kaiwei Lin; Zheng Chen 012; Chen Yang; Junji Yu; Zan Wang; Junjie Chen 003 (CoRR, 2025)

Symmetric Behavior Regularization via Taylor Expansion of Symmetry. - Lingwei Zhu; Zheng Chen 012; Han Wang; Yukie Nagai (CoRR, 2025)