Ueda, Masahito

9 publications

ICLR 2023 What Shapes the Loss Landscape of Self Supervised Learning? Liu Ziyin, Ekdeep Singh Lubana, Masahito Ueda, Hidenori Tanaka

ICLR 2022 Convergent and Efficient Deep Q Learning Algorithm Zhikang T. Wang, Masahito Ueda

NeurIPSW 2022 On Rotational Symmetry in the Loss Landscape of Self-Supervised Learning Liu Ziyin, Ekdeep Singh Lubana, Masahito Ueda, Hidenori Tanaka

ICML 2022 Power-Law Escape Rate of SGD Takashi Mori, Liu Ziyin, Kangqiao Liu, Masahito Ueda

ICLR 2022 SGD Can Converge to Local Maxima Liu Ziyin, Botao Li, James B Simon, Masahito Ueda

ICLR 2022 Strength of Minibatch Noise in SGD Liu Ziyin, Kangqiao Liu, Takashi Mori, Masahito Ueda

ICML 2021 Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent Kangqiao Liu, Liu Ziyin, Masahito Ueda

NeurIPS 2020 Neural Networks Fail to Learn Periodic Functions and How to Fix It Liu Ziyin, Tilman Hartwig, Masahito Ueda

NeurIPS 2019 Deep Gamblers: Learning to Abstain with Portfolio Theory Ziyin Liu, Zhikang Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, Masahito Ueda