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2020 – today
- 2025
[j2]Lennart Dabelow
, Masahito Ueda:
Symbolic equation solving via reinforcement learning. Neurocomputing 613: 128732 (2025)- 2024
- [i21]Lennart Dabelow, Masahito Ueda:
Symbolic Equation Solving via Reinforcement Learning. CoRR abs/2401.13447 (2024) - 2023
- [c8]Liu Ziyin, Ekdeep Singh Lubana, Masahito Ueda, Hidenori Tanaka:
What shapes the loss landscape of self supervised learning? ICLR 2023 - [i20]Liu Ziyin, Botao Li, Tomer Galanti, Masahito Ueda:
The Probabilistic Stability of Stochastic Gradient Descent. CoRR abs/2303.13093 (2023) - [i19]Liu Ziyin, Hongchao Li, Masahito Ueda:
Law of Balance and Stationary Distribution of Stochastic Gradient Descent. CoRR abs/2308.06671 (2023) - 2022
- [c7]Liu Ziyin, Kangqiao Liu, Takashi Mori, Masahito Ueda:
Strength of Minibatch Noise in SGD. ICLR 2022 - [c6]Liu Ziyin, Botao Li, James B. Simon, Masahito Ueda:
SGD Can Converge to Local Maxima. ICLR 2022 - [c5]Zhikang T. Wang, Masahito Ueda:
Convergent and Efficient Deep Q Learning Algorithm. ICLR 2022 - [c4]Takashi Mori, Liu Ziyin, Kangqiao Liu, Masahito Ueda:
Power-Law Escape Rate of SGD. ICML 2022: 15959-15975 - [i18]Takashi Mori, Masahito Ueda:
Interplay between depth of neural networks and locality of target functions. CoRR abs/2201.12082 (2022) - [i17]Liu Ziyin, Hanlin Zhang, Xiangming Meng, Yuting Lu, Eric P. Xing, Masahito Ueda:
Stochastic Neural Networks with Infinite Width are Deterministic. CoRR abs/2201.12724 (2022) - [i16]Liu Ziyin, Masahito Ueda:
Exact Phase Transitions in Deep Learning. CoRR abs/2205.12510 (2022) - [i15]Lennart Dabelow, Masahito Ueda:
Three Learning Stages and Accuracy-Efficiency Tradeoff of Restricted Boltzmann Machines. CoRR abs/2209.00873 (2022) - [i14]Liu Ziyin, Ekdeep Singh Lubana, Masahito Ueda, Hidenori Tanaka:
What shapes the loss landscape of self-supervised learning? CoRR abs/2210.00638 (2022) - 2021
- [c3]Kangqiao Liu, Liu Ziyin, Masahito Ueda:
Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent. ICML 2021: 7045-7056 - [i13]Liu Ziyin, Kangqiao Liu, Takashi Mori, Masahito Ueda:
On Minibatch Noise: Discrete-Time SGD, Overparametrization, and Bayes. CoRR abs/2102.05375 (2021) - [i12]Takashi Mori, Liu Ziyin, Kangqiao Liu, Masahito Ueda:
Logarithmic landscape and power-law escape rate of SGD. CoRR abs/2105.09557 (2021) - [i11]Zhikang T. Wang, Masahito Ueda:
A Convergent and Efficient Deep Q Network Algorithm. CoRR abs/2106.15419 (2021) - [i10]Liu Ziyin, Botao Li, Masahito Ueda:
SGD May Never Escape Saddle Points. CoRR abs/2107.11774 (2021) - 2020
- [c2]Liu Ziyin, Tilman Hartwig, Masahito Ueda:
Neural Networks Fail to Learn Periodic Functions and How to Fix It. NeurIPS 2020 - [i9]Liu Ziyin, Zhikang Wang, Masahito Ueda:
LaProp: a Better Way to Combine Momentum with Adaptive Gradient. CoRR abs/2002.04839 (2020) - [i8]Liu Ziyin, Blair Chen, Ru Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, Masahito Ueda:
Learning Not to Learn in the Presence of Noisy Labels. CoRR abs/2002.06541 (2020) - [i7]Liu Ziyin, Zihao Wang, Makoto Yamada, Masahito Ueda:
Volumization as a Natural Generalization of Weight Decay. CoRR abs/2003.11243 (2020) - [i6]Takashi Mori, Masahito Ueda:
Is deeper better? It depends on locality of relevant features. CoRR abs/2005.12488 (2020) - [i5]Liu Ziyin, Tilman Hartwig, Masahito Ueda:
Neural Networks Fail to Learn Periodic Functions and How to Fix It. CoRR abs/2006.08195 (2020) - [i4]Takashi Mori, Masahito Ueda:
Improved generalization by noise enhancement. CoRR abs/2009.13094 (2020) - [i3]Kangqiao Liu, Liu Ziyin, Masahito Ueda:
Stochastic Gradient Descent with Large Learning Rate. CoRR abs/2012.03636 (2020)
2010 – 2019
- 2019
- [c1]Liu Ziyin, Zhikang Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, Masahito Ueda:
Deep Gamblers: Learning to Abstain with Portfolio Theory. NeurIPS 2019: 10622-10632 - [i2]Liu Ziyin, Zhikang Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, Masahito Ueda:
Deep Gamblers: Learning to Abstain with Portfolio Theory. CoRR abs/1907.00208 (2019) - [i1]Zhikang Wang, Yuto Ashida, Masahito Ueda:
Deep Reinforcement Learning Control of Quantum Cartpoles. CoRR abs/1910.09200 (2019)
2000 – 2009
- 2003
- [j1]Hiroaki Terashima, Masahito Ueda:
Einstein-Podolsky-Rosen correlation seen from moving observers. Quantum Inf. Comput. 3(3): 224-228 (2003)
Coauthor Index
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