Masahito Ueda

According to our database, Masahito Ueda authored at least 27 papers between 2003 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Symbolic Equation Solving via Reinforcement Learning.

Lennart Dabelow, Masahito Ueda

CoRR, 2024

2023

Law of Balance and Stationary Distribution of Stochastic Gradient Descent.

Ziyin Liu, Hongchao Li, Masahito Ueda

CoRR, 2023

The Probabilistic Stability of Stochastic Gradient Descent.

Ziyin Liu, Botao Li, Tomer Galanti, Masahito Ueda

CoRR, 2023

What shapes the loss landscape of self supervised learning?

Ziyin Liu, Ekdeep Singh Lubana, Masahito Ueda, Hidenori Tanaka

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Three Learning Stages and Accuracy-Efficiency Tradeoff of Restricted Boltzmann Machines.

Lennart Dabelow, Masahito Ueda

CoRR, 2022

Exact Phase Transitions in Deep Learning.

Ziyin Liu, Masahito Ueda

CoRR, 2022

Stochastic Neural Networks with Infinite Width are Deterministic.

Ziyin Liu, Hanlin Zhang, Xiangming Meng, Yuting Lu, Eric P. Xing, Masahito Ueda

CoRR, 2022

Interplay between depth of neural networks and locality of target functions.

Takashi Mori, Masahito Ueda

CoRR, 2022

Power-Law Escape Rate of SGD.

Takashi Mori, Ziyin Liu, Kangqiao Liu, Masahito Ueda

Proceedings of the International Conference on Machine Learning, 2022

Convergent and Efficient Deep Q Learning Algorithm.

Zhikang T. Wang, Masahito Ueda

Proceedings of the Tenth International Conference on Learning Representations, 2022

SGD Can Converge to Local Maxima.

Ziyin Liu, Botao Li, James B. Simon, Masahito Ueda

Proceedings of the Tenth International Conference on Learning Representations, 2022

Strength of Minibatch Noise in SGD.

Ziyin Liu, Kangqiao Liu, Takashi Mori, Masahito Ueda

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

SGD May Never Escape Saddle Points.

Ziyin Liu, Botao Li, Masahito Ueda

CoRR, 2021

A Convergent and Efficient Deep Q Network Algorithm.

Zhikang T. Wang, Masahito Ueda

CoRR, 2021

Logarithmic landscape and power-law escape rate of SGD.

Takashi Mori, Ziyin Liu, Kangqiao Liu, Masahito Ueda

CoRR, 2021

On Minibatch Noise: Discrete-Time SGD, Overparametrization, and Bayes.

Ziyin Liu, Kangqiao Liu, Takashi Mori, Masahito Ueda

CoRR, 2021

Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent.

Kangqiao Liu, Ziyin Liu, Masahito Ueda

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Stochastic Gradient Descent with Large Learning Rate.

Kangqiao Liu, Ziyin Liu, Masahito Ueda

CoRR, 2020

Improved generalization by noise enhancement.

Takashi Mori, Masahito Ueda

CoRR, 2020

Is deeper better? It depends on locality of relevant features.

Takashi Mori, Masahito Ueda

CoRR, 2020

Volumization as a Natural Generalization of Weight Decay.

Ziyin Liu, Zihao Wang, Makoto Yamada, Masahito Ueda

CoRR, 2020

Learning Not to Learn in the Presence of Noisy Labels.

Ziyin Liu, Blair Chen, Ru Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, Masahito Ueda

CoRR, 2020

LaProp: a Better Way to Combine Momentum with Adaptive Gradient.

Ziyin Liu, Zhikang Wang, Masahito Ueda

CoRR, 2020

Neural Networks Fail to Learn Periodic Functions and How to Fix It.

Ziyin Liu, Tilman Hartwig, Masahito Ueda

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Deep Reinforcement Learning Control of Quantum Cartpoles.

Zhikang Wang, Yuto Ashida, Masahito Ueda

CoRR, 2019

Deep Gamblers: Learning to Abstain with Portfolio Theory.

Ziyin Liu, Zhikang Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, Masahito Ueda

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2003

Einstein-Podolsky-Rosen correlation seen from moving observers.

Hiroaki Terashima, Masahito Ueda

Quantum Inf. Comput., 2003