Niko Yasui
I am a MSc student under Martha White at the University of Alberta. My current research is on comparing exploration methods in reinforcement learning to better understand their fundamental mechanisms. More broadly, I study how the best way to approach learn and make decisions changes across situations, especially when a group of human or computational agents are learning and making decisions simultaneously. Most of my work is based on concepts from reinforcement learning and game theory.
2017 - Present, M.Sc. student in Computing Science, University of Alberta.
2013 - 2017, B.Sc. in Statistics and Computer Science, McGill University.
Yasui N, Lim S, Linke C, White A, White M, An Empirical and Conceptual Categorization of Value-based Exploration Methods. 2nd Annual Workshop on Exploration in Reinforcement Learning at ICML, 2019.
Yasui N, Vogiatzis C, Yoshida R, Fukumizu K, imPhy: Imputing Phylogenetic Trees with Missing Information using Mathematical Programming. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018.
Chen HY, Dufresne L, Burr H, Ambikkumar A, Yasui N, Luk K, Ranatunga DK, Whitmer RA, Lathrop M, Engert JC, Thanassoulis G., Association of LPA Variants With Aortic Stenosis: A Large-Scale Study Using Diagnostic and Procedural Codes From Electronic Health Records. JAMA Cardiology, 2017.
yasui@ualberta.ca
Last updated September 2019. [Download]