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2020 – today
- 2022
[c16]Takuya Hiraoka, Takahisa Imagawa, Taisei Hashimoto, Takashi Onishi, Yoshimasa Tsuruoka:
Dropout Q-Functions for Doubly Efficient Reinforcement Learning. ICLR 2022- [c15]Nicolas Bougie, Takashi Onishi, Yoshimasa Tsuruoka:
Local Control is All You Need: Decentralizing and Coordinating Reinforcement Learning for Large-Scale Process Control. SICE 2022: 468-474 - [i10]Shumpei Kubosawa, Takashi Onishi, Makoto Sakahara, Yoshimasa Tsuruoka:
Railway Operation Rescheduling System via Dynamic Simulation and Reinforcement Learning. CoRR abs/2201.06276 (2022) - [i9]Shumpei Kubosawa, Takashi Onishi, Yoshimasa Tsuruoka:
Soft Sensors and Process Control using AI and Dynamic Simulation. CoRR abs/2208.04373 (2022) - 2021
- [c14]Takuya Hiraoka, Takahisa Imagawa, Voot Tangkaratt, Takayuki Osa, Takashi Onishi, Yoshimasa Tsuruoka:
Meta-Model-Based Meta-Policy Optimization. ACML 2021: 129-144 - [c13]Shumpei Kubosawa, Takashi Onishi, Yoshimasa Tsuruoka:
Non-steady-state Control under Disturbances: Navigating Plant Operation via Simulation-Based Reinforcement Learning. SICE 2021: 799-806 - [i8]Takuya Hiraoka, Takahisa Imagawa, Taisei Hashimoto, Takashi Onishi, Yoshimasa Tsuruoka:
Dropout Q-Functions for Doubly Efficient Reinforcement Learning. CoRR abs/2110.02034 (2021) - 2020
- [i7]Takuya Hiraoka, Takahisa Imagawa, Voot Tangkaratt, Takayuki Osa, Takashi Onishi, Yoshimasa Tsuruoka:
Meta-Model-Based Meta-Policy Optimization. CoRR abs/2006.02608 (2020)
2010 – 2019
- 2019
- [j4]Takashi Onishi, Teppei Takashima, Moriaki Sakakura, Koichi Sakamoto, Kazuhito Ohashi:
Improvement of the Form Accuracy of a Slender Workpiece in Cylindrical Traverse Grinding. Int. J. Autom. Technol. 13(6): 728-735 (2019) - [c12]Seydou Ba, Takuya Hiraoka, Takashi Onishi, Toru Nakata, Yoshimasa Tsuruoka:
Monte Carlo Tree Search with Variable Simulation Periods for Continuously Running Tasks. ICTAI 2019: 416-423 - [c11]Takuya Hiraoka, Takahisa Imagawa, Tatsuya Mori, Takashi Onishi, Yoshimasa Tsuruoka:
Learning Robust Options by Conditional Value at Risk Optimization. NeurIPS 2019: 2615-2625 - [i6]Shumpei Kubosawa, Takashi Onishi, Yoshimasa Tsuruoka:
Synthesizing Chemical Plant Operation Procedures using Knowledge, Dynamic Simulation and Deep Reinforcement Learning. CoRR abs/1903.02183 (2019) - [i5]Takuya Hiraoka, Takahisa Imagawa, Tatsuya Mori, Takashi Onishi, Yoshimasa Tsuruoka:
Learning Robust Options by Conditional Value at Risk Optimization. CoRR abs/1905.09191 (2019) - 2018
- [i4]Shota Motoura, Kazeto Yamamoto, Shumpei Kubosawa, Takashi Onishi:
Translating MFM into FOL: towards plant operation planning. CoRR abs/1806.07037 (2018) - [i3]Kazeto Yamamoto, Takashi Onishi, Yoshimasa Tsuruoka:
Hierarchical Reinforcement Learning with Abductive Planning. CoRR abs/1806.10792 (2018) - [i2]Seydou Ba, Takuya Hiraoka, Takashi Onishi, Toru Nakata, Yoshimasa Tsuruoka:
Monte Carlo Tree Search with Scalable Simulation Periods for Continuously Running Tasks. CoRR abs/1809.02378 (2018) - [i1]Takuya Hiraoka, Takashi Onishi, Takahisa Imagawa, Yoshimasa Tsuruoka:
Refining Manually-Designed Symbol Grounding and High-Level Planning by Policy Gradients. CoRR abs/1810.00177 (2018) - 2017
- [c10]Shohei Higashiyama, Kunihiko Sadamasa, Takashi Onishi, Yotaro Watanabe:
Event Relation Acquisition Using Dependency Patterns and Confidence-Weighted Co-occurrence Statistics. FedCSIS 2017: 339-345 - 2013
- [c9]Daniel Andrade, Masaaki Tsuchida, Takashi Onishi, Kai Ishikawa:
Synonym Acquisition Using Bilingual Comparable Corpora. IJCNLP 2013: 1077-1081 - [c8]Aobo Wang, Min-Yen Kan, Daniel Andrade, Takashi Onishi, Kai Ishikawa:
Chinese Informal Word Normalization: an Experimental Study. IJCNLP 2013 - [c7]Daniel Andrade, Masaaki Tsuchida, Takashi Onishi, Kai Ishikawa:
Translation Acquisition Using Synonym Sets. HLT-NAACL 2013: 655-660 - [c6]Daniel Andrade, Masaaki Tsuchida, Takashi Onishi, Kai Ishikawa:
Detecting Contradiction in Text by Using Lexical Mismatch and Structural Similarity. NTCIR 2013 - 2012
- [j3]Isao Goto, Masao Utiyama, Takashi Onishi, Eiichiro Sumita:
An Empirical Comparison of Parsers in Constraining Reordering for E-J Patent Machine Translation. J. Inf. Process. 20(4): 871-882 (2012) - 2011
- [j2]Takashi Onishi, Masao Utiyama, Eiichiro Sumita:
Paraphrase Lattice for Statistical Machine Translation. IEICE Trans. Inf. Syst. 94-D(6): 1299-1305 (2011) - [c5]Takashi Onishi, Masao Utiyama, Eiichiro Sumita:
Reordering Constraint Based on Document-Level Context. ACL (2) 2011: 434-438 - [c4]Chooi-Ling Goh, Takashi Onishi, Eiichiro Sumita:
Rule-based Reordering Constraints for Phrase-based SMT. EAMT 2011 - [c3]Isao Goto, Masao Utiyama, Takashi Onishi, Eiichiro Sumita:
A Comparison Study of Parsers for Patent Machine Translation. MTSummit 2011 - [c2]Masao Utiyama, Graham Neubig, Takashi Onishi, Eiichiro Sumita:
Searching Translation Memories for Paraphrases. MTSummit 2011 - 2010
- [c1]Takashi Onishi, Masao Utiyama, Eiichiro Sumita:
Paraphrase Lattice for Statistical Machine Translation. ACL (2) 2010: 1-5
2000 – 2009
- 2007
- [j1]Ademola K. Braimoh, Takashi Onishi:
Geostatistical techniques for incorporating spatial correlation into land use change models. Int. J. Appl. Earth Obs. Geoinformation 9(4): 438-446 (2007)
Coauthor Index
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last updated on 2023-09-08 10:03 CEST by the dblp team
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