Norio Kosaka(小坂 紀夫)
email: kosakaboat[at]

CV | Scholar | Github | LinkedIn

I finished MSc Machine Learning with Distinction at Royal Holloway University of London and worked on the intersection of Reinforcement Learning & Robotics for my Master Thesis. I am proud to be advised by Prof. Chris Watkins with the thesis.

My research interests: Model-based Planning(e.g., MPC) in RL, Offline Policy Evaluation(aka Counterfactual Evaluation), Listwise Recommender Systems.

My team at NAVER hosts a weekly study group in which we discuss a variety of ML topics, so please let me know if you are interested. Any topic is welcome so that let's discuss together!!

  Work Experience

[NEW] Know Your Action Set: Learning Action Relations for Reinforcement Learning
Ayush Jain*, Norio Kosaka*, Kyung-Min Kim, Joseph J Lim
International Conference on Learning Representations 2022, Apr. 2022


PlaNet of the Bayesians: Reconsidering and Improving Deep Planning Network by Incorporating Bayesian Inference
Masashi Okada, Norio Kosaka, Tadahiro Taniguchi
International Conference on Intelligent Robots and Systems(IROS) 2020, USA, Oct. 2020


Has it explored enough
Norio Kosaka
Master's Thesis at Royal Holloway, University of London, Sep. 2019

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