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ORCIDLingwei Zhu
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2020 – today
- 2024
[j5]Lingwei Zhu, Matthew Schlegel, Han Wang, Martha White:
Offline Reinforcement Learning via Tsallis Regularization. Trans. Mach. Learn. Res. 2024 (2024)- [i16]Lingwei Zhu, Haseeb Shah, Han Wang, Martha White:
q-exponential family for policy optimization. CoRR abs/2408.07245 (2024) - [i15]Xihao Piao, Pei Gao, Zheng Chen, Lingwei Zhu, Yasuko Matsubara, Yasushi Sakurai:
BEHRNOULLI: A Binary EHR Data-Oriented Medication Recommendation System. CoRR abs/2408.09410 (2024) - 2023
- [j4]Zheng Chen
, Ziwei Yang, Lingwei Zhu, Peng Gao, Takashi Matsubara, Shigehiko Kanaya, Md. Altaf-Ul-Amin:
Learning vector quantized representation for cancer subtypes identification. Comput. Methods Programs Biomed. 236: 107543 (2023) - [j3]Lingwei Zhu, Takamitsu Matsubara:
Cautious policy programming: exploiting KL regularization for monotonic policy improvement in reinforcement learning. Mach. Learn. 112(11): 4527-4562 (2023) - [j2]Yuki Kadokawa, Lingwei Zhu, Yoshihisa Tsurumine, Takamitsu Matsubara:
Cyclic policy distillation: Sample-efficient sim-to-real reinforcement learning with domain randomization. Robotics Auton. Syst. 165: 104425 (2023) - [c12]Honglin Shu, Pei Gao, Lingwei Zhu, Zheng Chen, Yasuko Matsubara, Yasushi Sakurai:
Drugs Resistance Analysis from Scarce Health Records via Multi-task Graph Representation. ADMA (3) 2023: 103-117 - [c11]Lingwei Zhu, Zheng Chen, Matthew Schlegel, Martha White:
General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence. NeurIPS 2023 - [c10]Zheng Chen, Lingwei Zhu, Haohui Jia, Takashi Matsubara:
A Two-View EEG Representation for Brain Cognition by Composite Temporal-Spatial Contrastive Learning. SDM 2023: 334-342 - [i14]Lingwei Zhu, Zheng Chen, Takamitsu Matsubara, Martha White:
Generalized Munchausen Reinforcement Learning using Tsallis KL Divergence. CoRR abs/2301.11476 (2023) - [i13]Honglin Shu, Pei Gao, Lingwei Zhu, Zheng Chen:
Drugs Resistance Analysis from Scarce Health Records via Multi-task Graph Representation. CoRR abs/2302.11231 (2023) - 2022
- [j1]Lingwei Zhu, Go Takami, Mizuo Kawahara, Hiroaki Kanokogi, Takamitsu Matsubara:
Alleviating parameter-tuning burden in reinforcement learning for large-scale process control. Comput. Chem. Eng. 158: 107658 (2022) - [c9]Ziwei Yang, Lingwei Zhu, Chen Li, Zheng Chen, Naoki Ono, Md. Altaf-Ul-Amin, Shigehiko Kanaya:
Hierarchical Categorical Generative Modeling for Multi-omics Cancer Subtyping. BIBM 2022: 1350-1355 - [c8]Ziwei Yang, Lingwei Zhu, Zheng Chen, Ming Huang, Naoaki Ono, Md. Altaf-Ul-Amin, Shigehiko Kanaya:
Cancer Subtyping via Embedded Unsupervised Learning on Transcriptomics Data. EMBC 2022: 1113-1116 - [c7]Lingwei Zhu, Ziwei Yang, Koki Odani, Guang Shi, Yirong Kan, Zheng Chen, Renyuan Zhang:
Adaptive Spike-Like Representation of EEG Signals for Sleep Stages Scoring. EMBC 2022: 4453-4456 - [c6]Zheng Chen, Lingwei Zhu, Ziwei Yang, Renyuan Zhang:
Multi-Tier Platform for Cognizing Massive Electroencephalogram. IJCAI 2022: 2464-2470 - [c5]Zheng Chen, Lingwei Zhu, Ziwei Yang, Takashi Matsubara:
Automated Cancer Subtyping via Vector Quantization Mutual Information Maximization. ECML/PKDD (1) 2022: 88-103 - [i12]Ziwei Yang, Lingwei Zhu, Zheng Chen, Ming Huang, Naoaki Ono, Md. Altaf-Ul-Amin, Shigehiko Kanaya:
Cancer Subtyping via Embedded Unsupervised Learning on Transcriptomics Data. CoRR abs/2204.02278 (2022) - [i11]Lingwei Zhu, Koki Odani, Ziwei Yang, Guang Shi, Yirong Kan, Zheng Chen, Renyuan Zhang:
Adaptive Spike-Like Representation of EEG Signals for Sleep Stages Scoring. CoRR abs/2204.03565 (2022) - [i10]Zheng Chen, Lingwei Zhu, Ziwei Yang, Renyuan Zhang:
Multi-Tier Platform for Cognizing Massive Electroencephalogram. CoRR abs/2204.09840 (2022) - [i9]Lingwei Zhu, Zheng Chen, Eiji Uchibe, Takamitsu Matsubara:
q-Munchausen Reinforcement Learning. CoRR abs/2205.07467 (2022) - [i8]Lingwei Zhu, Zheng Chen, Eiji Uchibe, Takamitsu Matsubara:
Enforcing KL Regularization in General Tsallis Entropy Reinforcement Learning via Advantage Learning. CoRR abs/2205.07885 (2022) - [i7]Zheng Chen, Lingwei Zhu, Ziwei Yang, Takashi Matsubara:
Automated Cancer Subtyping via Vector Quantization Mutual Information Maximization. CoRR abs/2206.10801 (2022) - [i6]Zheng Chen, Ziwei Yang, Lingwei Zhu, Guang Shi, Kun Yue, Takashi Matsubara, Shigehiko Kanaya, Md. Altaf-Ul-Amin:
Cancer Subtyping by Improved Transcriptomic Features Using Vector Quantized Variational Autoencoder. CoRR abs/2207.09783 (2022) - [i5]Yuki Kadokawa, Lingwei Zhu, Yoshihisa Tsurumine, Takamitsu Matsubara:
Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement Learning with Domain Randomization. CoRR abs/2207.14561 (2022) - 2021
- [c4]Lingwei Zhu, Toshinori Kitamura, Takamitsu Matsubara:
Cautious Actor-Critic. ACML 2021: 220-235 - [c3]Toshinori Kitamura, Lingwei Zhu, Takamitsu Matsubara:
Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning. ACML 2021: 918-931 - [i4]Lingwei Zhu, Toshinori Kitamura, Takamitsu Matsubara:
Cautious Actor-Critic. CoRR abs/2107.05217 (2021) - [i3]Lingwei Zhu, Toshinori Kitamura, Takamitsu Matsubara:
Cautious Policy Programming: Exploiting KL Regularization in Monotonic Policy Improvement for Reinforcement Learning. CoRR abs/2107.05798 (2021) - [i2]Toshinori Kitamura, Lingwei Zhu, Takamitsu Matsubara:
Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning. CoRR abs/2107.07659 (2021) - 2020
- [c2]Lingwei Zhu, Yunduan Cui, Takamitsu Matsubara:
Dynamic Actor-Advisor Programming for Scalable Safe Reinforcement Learning. ICRA 2020: 10681-10687 - [i1]Lingwei Zhu, Takamitsu Matsubara:
Ensuring Monotonic Policy Improvement in Entropy-regularized Value-based Reinforcement Learning. CoRR abs/2008.10806 (2020)
2010 – 2019
- 2018
- [c1]Yunduan Cui, Lingwei Zhu, Morihiro Fujisaki, Hiroaki Kanokogi, Takamitsu Matsubara:
Factorial Kernel Dynamic Policy Programming for Vinyl Acetate Monomer Plant Model Control. CASE 2018: 304-309
Coauthor Index
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last updated on 2024-09-26 01:54 CEST by the dblp team
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