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Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?

K. Ota, T. Oiki, D. Jha, T. Mariyama, и D. Nikovski. ICML, том 119 из Proceedings of Machine Learning Research, стр. 7424-7433. PMLR, (2020)

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Michitaka Ota

Yoichi Otani

Ljiljana Otasevic-Wieschalla

Guillermo Otalora

Antje Ota

Другие публикации лиц с тем же именем

Data-Efficient Learning for Complex and Real-Time Physical Problem Solving Using Augmented Simulation.K. Ota, D. Jha, D. Romeres, J. van Baar, K. Smith, T. Semitsu, T. Oiki, A. Sullivan, D. Nikovski, и J. Tenenbaum. IEEE Robotics Autom. Lett., 6 (2): 4241-4248 (2021)Style-transfer based Speech and Audio-visual Scene understanding for Robot Action Sequence Acquisition from Videos.C. Hori, P. Peng, D. Harwath, X. Liu, K. Ota, S. Jain, R. Corcodel, D. Jha, D. Romeres, и J. Roux. INTERSPEECH, стр. 4663-4667. ISCA, (2023)Towards Human-Level Learning of Complex Physical Puzzles.K. Ota, D. Jha, D. Romeres, J. van Baar, K. Smith, T. Semitsu, T. Oiki, A. Sullivan, D. Nikovski, и J. Tenenbaum. CoRR, (2020)OPIRL: Sample Efficient Off-Policy Inverse Reinforcement Learning via Distribution Matching.H. Hoshino, K. Ota, A. Kanezaki, и R. Yokota. ICRA, стр. 448-454. IEEE, (2022)Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path.K. Ota, Y. Sasaki, D. Jha, Y. Yoshiyasu, и A. Kanezaki. IROS, стр. 6061-6068. IEEE, (2020)Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?K. Ota, T. Oiki, D. Jha, T. Mariyama, и D. Nikovski. ICML, том 119 из Proceedings of Machine Learning Research, стр. 7424-7433. PMLR, (2020)Object Memory Transformer for Object Goal Navigation.R. Fukushima, K. Ota, A. Kanezaki, Y. Sasaki, и Y. Yoshiyasu. ICRA, стр. 11288-11294. IEEE, (2022)Tactile-Filter: Interactive Tactile Perception for Part Mating.K. Ota, D. Jha, H. Tung, и J. Tenenbaum. Robotics: Science and Systems, (2023)Deep Reactive Planning in Dynamic Environments.K. Ota, D. Jha, T. Onishi, A. Kanezaki, Y. Yoshiyasu, Y. Sasaki, T. Mariyama, и D. Nikovski. CoRL, том 155 из Proceedings of Machine Learning Research, стр. 1943-1957. PMLR, (2020)Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning.K. Ota, D. Jha, T. Oiki, M. Miura, T. Nammoto, D. Nikovski, и T. Mariyama. IROS, стр. 3487-3494. IEEE, (2019)

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