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ORCIDTetsuro Morimura
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Journal Articles
- 2024
[j6]Satoshi Hayakawa, Tetsuro Morimura:
Policy Gradient with Kernel Quadrature. Trans. Mach. Learn. Res. 2024 (2024)- 2017
- [j5]Tsuyoshi Idé
, Takayuki Katsuki, Tetsuro Morimura, Robert J. T. Morris:
City-Wide Traffic Flow Estimation From a Limited Number of Low-Quality Cameras. IEEE Trans. Intell. Transp. Syst. 18(4): 950-959 (2017) - [j4]Takayuki Katsuki, Tetsuro Morimura, Masato Inoue:
Traffic Velocity Estimation From Vehicle Count Sequences. IEEE Trans. Intell. Transp. Syst. 18(7): 1700-1712 (2017) - 2010
- [j3]Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashima, Tetsuro Morimura:
Least Absolute Policy Iteration-A Robust Approach to Value Function Approximation. IEICE Trans. Inf. Syst. 93-D(9): 2555-2565 (2010) - [j2]Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto, Jan Peters, Kenji Doya:
Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning. Neural Comput. 22(2): 342-376 (2010) - 2008
- [j1]Tetsuro Morimura, Eiji Uchibe, Kenji Doya:
Natural actor-critic with baseline adjustment for variance reduction. Artif. Life Robotics 13(1): 275-279 (2008)
Conference and Workshop Papers
- 2024
- [c29]Yuu Jinnai, Ukyo Honda, Tetsuro Morimura, Peinan Zhang:
Generating Diverse and High-Quality Texts by Minimum Bayes Risk Decoding. ACL (Findings) 2024: 8494-8525 - [c28]Tetsuro Morimura, Mitsuki Sakamoto, Yuu Jinnai, Kenshi Abe, Kaito Ariu:
Filtered Direct Preference Optimization. EMNLP 2024: 22729-22770 - [c27]Riku Togashi, Tatsushi Oka, Naoto Ohsaka, Tetsuro Morimura:
Safe Collaborative Filtering. ICLR 2024 - [c26]Yuu Jinnai, Tetsuro Morimura, Ukyo Honda, Kaito Ariu, Kenshi Abe:
Model-Based Minimum Bayes Risk Decoding for Text Generation. ICML 2024 - [c25]Hao Wang, Tetsuro Morimura, Ukyo Honda, Daisuke Kawahara:
Reinforcement Learning for Edit-Based Non-Autoregressive Neural Machine Translation. NAACL (Student Research Workshop) 2024: 212-218 - [c24]Atsumoto Ohashi, Ukyo Honda, Tetsuro Morimura, Yuu Jinnai:
On the True Distribution Approximation of Minimum Bayes-Risk Decoding. NAACL (Short Papers) 2024: 459-468 - [c23]Tetsuro Morimura, Kazuhiro Ota, Kenshi Abe, Peinan Zhang:
Policy Gradient Algorithms with Monte Carlo Tree Learning for Non-Markov Decision Processes. RLC 2024: 1351-1376 - 2016
- [c22]Daisuke Sato, Tetsuro Morimura, Takayuki Katsuki, Yosuke Toyota, Tsuneo Kato, Hironobu Takagi:
Automated help system for novice older users from touchscreen gestures. ICPR 2016: 3073-3078 - [c21]Takayuki Katsuki, Tetsuro Morimura, Tsuyoshi Idé:
Unsupervised object counting without object recognition. ICPR 2016: 3627-3632 - [c20]Yasunori Yamada, Tetsuro Morimura:
Weight Features for Predicting Future Model Performance of Deep Neural Networks. IJCAI 2016: 2231-2237 - 2015
- [c19]Satoshi Hara, Tetsuro Morimura, Toshihiro Takahashi, Hiroki Yanagisawa, Taiji Suzuki:
A Consistent Method for Graph Based Anomaly Localization. AISTATS 2015 - [c18]Rikiya Takahashi, Tetsuro Morimura:
Predicting Preference Reversals via Gaussian Process Uncertainty Aversion. AISTATS 2015 - 2014
- [c17]Tetsuro Morimura, Takayuki Osogami, Tomoyuki Shirai:
Mixing-Time Regularized Policy Gradient. AAAI 2014: 1997-2003 - [c16]Bin Tong, Tetsuro Morimura, Einoshin Suzuki, Tsuyoshi Idé:
Probabilistic Two-Level Anomaly Detection for Correlated Systems. ECAI 2014: 1109-1110 - [c15]Satoshi Hara, Rudy Raymond, Tetsuro Morimura, Hidemasa Muta:
Predicting halfway through simulation: early scenario evaluation using intermediate features of agent-based simulations. WSC 2014: 334-343 - [c14]Hidemasa Muta, Rudy Raymond, Satoshi Hara, Tetsuro Morimura:
A multi-objective genetic algorithm using intermediate features of simulations. WSC 2014: 793-804 - [c13]Kumiko Maeda, Tetsuro Morimura, Takayuki Katsuki, Masayoshi Teraguchi:
Frugal signal control using low resolution web-camera and traffic flow estimation. WSC 2014: 2082-2091 - 2013
- [c12]Tetsuro Morimura, Takayuki Osogami, Tsuyoshi Idé:
Solving inverse problem of Markov chain with partial observations. NIPS 2013: 1655-1663 - 2012
- [c11]Takayuki Osogami, Tetsuro Morimura:
Time-Consistency of Optimization Problems. AAAI 2012: 1945-1953 - [c10]Rudy Raymond, Tetsuro Morimura, Takayuki Osogami, Noriaki Hirosue:
Map matching with Hidden Markov Model on sampled road network. ICPR 2012: 2242-2245 - [c9]Tetsuro Morimura, Sei Kato:
Statistical Origin-destination generation with multiple sources. ICPR 2012: 3443-3446 - [c8]Shohei Hido, Tetsuro Morimura:
Temporal feature selection for time-series prediction. ICPR 2012: 3557-3560 - [c7]Rikiya Takahashi, Takayuki Osogami, Tetsuro Morimura:
Large-Scale Nonparametric Estimation of Vehicle Travel Time Distributions. SDM 2012: 12-23 - 2010
- [c6]Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka:
Nonparametric Return Distribution Approximation for Reinforcement Learning. ICML 2010: 799-806 - [c5]Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka:
Parametric Return Density Estimation for Reinforcement Learning. UAI 2010: 368-375 - [c4]Takamitsu Matsubara, Tetsuro Morimura, Jun Morimoto:
Adaptive Step-size Policy Gradients with Average Reward Metric. ACML 2010: 285-298 - 2009
- [c3]Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashima, Tetsuro Morimura:
Least absolute policy iteration for robust value function approximation. ICRA 2009: 2904-2909 - [c2]Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto, Kenji Doya:
A Generalized Natural Actor-Critic Algorithm. NIPS 2009: 1312-1320 - 2008
- [c1]Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto, Kenji Doya:
A New Natural Policy Gradient by Stationary Distribution Metric. ECML/PKDD (2) 2008: 82-97
Informal and Other Publications
- 2024
- [i15]Yuu Jinnai, Ukyo Honda, Tetsuro Morimura, Peinan Zhang:
Generating Diverse and High-Quality Texts by Minimum Bayes Risk Decoding. CoRR abs/2401.05054 (2024) - [i14]Tsunehiko Tanaka, Kenshi Abe, Kaito Ariu, Tetsuro Morimura, Edgar Simo-Serra:
Return-Aligned Decision Transformer. CoRR abs/2402.03923 (2024) - [i13]Atsumoto Ohashi, Ukyo Honda, Tetsuro Morimura, Yuu Jinnai:
On the True Distribution Approximation of Minimum Bayes-Risk Decoding. CoRR abs/2404.00752 (2024) - [i12]Yuu Jinnai, Tetsuro Morimura, Kaito Ariu, Kenshi Abe:
Regularized Best-of-N Sampling to Mitigate Reward Hacking for Language Model Alignment. CoRR abs/2404.01054 (2024) - [i11]Tetsuro Morimura, Mitsuki Sakamoto, Yuu Jinnai, Kenshi Abe, Kaito Ariu:
Filtered Direct Preference Optimization. CoRR abs/2404.13846 (2024) - [i10]Hao Wang, Tetsuro Morimura, Ukyo Honda, Daisuke Kawahara:
Reinforcement Learning for Edit-Based Non-Autoregressive Neural Machine Translation. CoRR abs/2405.01280 (2024) - 2023
- [i9]Riku Togashi, Tatsushi Oka, Naoto Ohsaka, Tetsuro Morimura:
Safe Collaborative Filtering. CoRR abs/2306.05292 (2023) - [i8]Sho Shimoyama, Tetsuro Morimura, Kenshi Abe, Toda Takamichi, Yuta Tomomatsu, Masakazu Sugiyama, Asahi Hentona, Yuuki Azuma, Hirotaka Ninomiya:
Why Guided Dialog Policy Learning performs well? Understanding the role of adversarial learning and its alternative. CoRR abs/2307.06721 (2023) - [i7]Yuu Jinnai, Tetsuro Morimura, Ukyo Honda:
On the Depth between Beam Search and Exhaustive Search for Text Generation. CoRR abs/2308.13696 (2023) - [i6]Satoshi Hayakawa, Tetsuro Morimura:
Policy Gradient with Kernel Quadrature. CoRR abs/2310.14768 (2023) - [i5]Yuu Jinnai, Tetsuro Morimura, Ukyo Honda, Kaito Ariu, Kenshi Abe:
Model-Based Minimum Bayes Risk Decoding. CoRR abs/2311.05263 (2023) - 2022
- [i4]Tetsuro Morimura, Kazuhiro Ota, Kenshi Abe, Peinan Zhang:
Policy Gradient Algorithms with Monte-Carlo Tree Search for Non-Markov Decision Processes. CoRR abs/2206.01011 (2022) - 2019
- [i3]Yachiko Obara, Tetsuro Morimura, Hiroki Yanagisawa:
Sampler for Composition Ratio by Markov Chain Monte Carlo. CoRR abs/1906.06663 (2019) - [i2]Kun Zhao, Takayuki Osogami, Tetsuro Morimura:
Visual analytics for team-based invasion sports with significant events and Markov reward process. CoRR abs/1907.01221 (2019) - 2012
- [i1]Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka:
Parametric Return Density Estimation for Reinforcement Learning. CoRR abs/1203.3497 (2012)
Coauthor Index
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