Kenji Kawaguchi. Deep Learning without Poor Local Minima.
In Advances in Neural Information Processing (NIPS), 2016.
[pdf] [BibTex] [Spotlight Video] [Talk] Selected for NIPS oral presentation (top 2% submissions)
Kenji Kawaguchi, Yu Maruyama and Xiaoyu Zheng. Global Continuous Optimization with Error Bound and Fast Convergence.
Journal of Artificial Intelligence Research (JAIR), 56: 153-195, 2016.
[pdf] [BibTex] [Code]
Xiaoyu Zheng, Hiroto Itoh, Kenji Kawaguchi, Hitoshi Tamaki and Yu Maruyama. Application of Bayesian nonparametric models to the uncertainty and sensitivity analysis of source term in a BWR severe accident.
Reliability Engineering & System Safety, 138: 253-262, 2015.
Jun Ishikawa, Kenji Kawaguchi and Yu Maruyama. Analysis for iodine release from unit 3 of Fukushima Dai-ichi nuclear power plant with consideration of water phase iodine chemistry.
Journal of Nuclear Science and Technology, 52(3):308-315, 2015.
Qianli Liao, Kenji Kawaguchi and Tomaso Poggio. Streaming Normalization: Towards Simpler and More Biologically-plausible Normalizations for Online and Recurrent Learning.
arXiv preprint arXiv:1610.06160, 2016.
Machine Learning, Deep Learning, Convex/Nonconvex Optimization, Bayesian Optimization, Model-based Reinforcement Learning
Massachusetts Institute of Technology 2016/02
M.S., Electrical Engineering and Computer Science
Advisors: Leslie Pack Kaelbling and Tomás Lozano-Pérez.
Thesis: Towards Practical Theory: Bayesian Optimization and Optimal Exploration
Funai Overseas Scholarship
April 2014 - August 2016
Nakajima Foundation Fellowship
Additional Honors & Awards