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Researcher, CyberAgent AI Lab
Artificial Intelligence, Reinforcement Learning, Classical Planning, Heuristic Search, Computer-Aided Diagnosis,
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Noda T, Jinnai Y, Tomii N, Azuma T. 2023. Blind Signal Separation for Fast Ultrasound Computed Tomography. arXiv 2304.14424 arXiv |
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Lecarpentier E, Abel D, Asadi K, Jinnai Y, Rachelson E, Littman Michael L. 2021. Lipschitz Lifelong Reinforcement Learning. Proc. 35th AAAI conference on Artificial Intelligence (AAAI-21) arXiv Poster Code |
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Y. Jinnai, J. Park, M.C. Machado, and G.D. Konidaris. Exploration in Reinforcement Learning with Deep Covering Options. Accepted, Proceedings of the Eighth International Conference on Learning Representations. (ICLR-20) PAPER |
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Wang L*, Zhao Y*, Jinnai Y, Tian Y, Fonseca R. 2020. AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search. Proc. 34th AAAI conference on Artificial Intelligence (AAAI-20) *These authors contributed equally to this work. PAPER CODE |
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Jinnai Y. Park JW, Abel D, Konidaris G. 2019. Discovering Options for Exploration by Minimizing Cover Time. Proc. 36th International Conference on Machine Learning. (ICML-19) PAPER CODE TALK |
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Jinnai Y, Abel D, Hershkowitz E, Littman M, Konidaris G. 2019. Finding Options that Minimize Planning Time. Proc. 36th International Conference on Machine Learning. (ICML-19) PAPER CODE TALK |
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Jinnai Y, Abel D, Park JW, Hershkowitz E, Littman M, Konidaris G. 2019. Skill Discovery with Well-Defined Objectives. ICLR Worshop on Structure and Priors in Reinforcement Learning. PAPER |
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Abel D, Arumugam D, Asadi K, Jinnai Y, Littman M, Wong L. S. 2019. State Abstraction as Compression in Apprenticeship Learning. Proc. 33rd AAAI Conference on Artificial Intelligence (AAAI-19). PAPER CODE |
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Abel D*, Jinnai Y*, Guo Y, Konidaris G, Littman M. 2018. Policy and Value Transfer for Lifelong Reinforcement Learning. Proc. 35th International Conference on Machine Learning. (ICML-18) *These authors contributed equally to this work. PAPER POSTER CODE TALK by D. Abel |
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Fukunaga A, Botea A, Jinnai Y, Kishimoto A. 2018. Parallel A* for State-Space Search. Handbook of Parallel Constraint Reasoning, Youssef Hamadi, Lakhdar Sais (eds.), Springer. ISBN 978-3-319-63515-6. BOOK |
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Jinnai Y, Fukunaga A. 2017. A Graph-Partitioning Based Approach for Parallel Best-First Search. ICAPS 2017 Workshop on Heuristic and Search for Domain-Independent Planning (HSDIP). PAPER SLIDES POSTER CODE |
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Jinnai Y, Fukunaga A. 2017. Learning to Prune Dominated Action Sequences in Online Black-box Planning. Proc. 31st AAAI Conference on Artificial Intelligence. (AAAI-17) PAPER SLIDES CODE |
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Jinnai Y, Fukunaga A. 2017. On Hash-Based Work Distribution Methods for Parallel Best-First Search. Journal of Artificial Intelligence Research. (JAIR) PAPER CODE |
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(Preprint) Fukunaga A., Botea A, Jinnai Y., Kishimoto A. 2017. A Survey of Parallel A*. arXiv 1708.05296 PAPER |
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Jinnai Y, Fukunaga A. 2016. Automated Creation of Efficient Work Distribution Functions for Parallel Best-First Search. Proc. 19th International Conference on Automated Planning and Scheduling. (ICAPS-16) PAPER SLIDES VIDEO CODE |
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Jinnai Y, Fukunaga A. 2016. Abstract Zobrist Hashing: An Efficient Work Distribution Method for Parallel Best-First Search. Proc. 30th AAAI Conference on Artificial Intelligence. (AAAI-16) PAPER POSTER CODE (PDDL) CODE (sliding-tile, path-finding, MSA) |
2016 Winter Semester (University of Tokyo)
Teaching assistant for Terakoya program, which is a program to walk through introductory level math and computer science for undergraduates at the University of Tokyo.
2016 Summer Semester (University of Tokyo)
I was working as a teaching assistant (TA) for information engineering at the University of Tokyo.
2015 Summer (Tama High School of Science and Technology) I was working as a part-time instructor at Tama High School of Science and Technology to teach scientific presentation.
2015 Winter Semester (University of Tokyo)
I was teaching introductory graph theory with flip-teaching style for Terakoya program at the University of Tokyo.
2015 Summer Semester (University of Tokyo)
I was a teaching assistant (TA) for first year seminar for science student at the University of Tokyo.
I was a teaching assistant (TA) for information engineering at the University of Tokyo.
Jan. 2018. Automated Deep Learning by Neural Architecture Search. National Institute of Information and Communications Technology, Japan.
Feb. 2017. Graph search algorithms for classical planning. Discrete Structure Manipulation System Project. Hokkaido University, Japan.