Ziyin Liu

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 41

Top Topics

Stochastic Gradient Descent

Perceptron Algorithm

Supervised Learning

Top Venues

Publications

Ziyin Liu
Symmetry Leads to Structured Constraint of Learning. CoRR (2023)
Ziyin Liu, Hongchao Li, Masahito Ueda
Law of Balance and Stationary Distribution of Stochastic Gradient Descent. CoRR (2023)
Ziyin Liu, Botao Li, Tomer Galanti, Masahito Ueda
The Probabilistic Stability of Stochastic Gradient Descent. CoRR (2023)
Ziyin Liu, Ekdeep Singh Lubana, Masahito Ueda, Hidenori Tanaka
What shapes the loss landscape of self supervised learning? ICLR (2023)
James B. Simon, Maksis Knutins, Ziyin Liu, Daniel Geisz, Abraham J. Fetterman, Joshua Albrecht
On the stepwise nature of self-supervised learning. CoRR (2023)
James B. Simon, Maksis Knutins, Ziyin Liu, Daniel Geisz, Abraham J. Fetterman, Joshua Albrecht
On the Stepwise Nature of Self-Supervised Learning. ICML (2023)
Ziyin Liu, Zihao Wang
spred: Solving L1 Penalty with SGD. ICML (2023)
Ziyin Liu, Botao Li, Xiangming Meng
Exact Solutions of a Deep Linear Network. CoRR (2022)
Ziyin Liu, Kangqiao Liu, Takashi Mori, Masahito Ueda
Strength of Minibatch Noise in SGD. ICLR (2022)
Zihao Wang, Ziyin Liu
Posterior Collapse of a Linear Latent Variable Model. NeurIPS (2022)
Ziyin Liu, Botao Li, James B Simon, Masahito Ueda
SGD Can Converge to Local Maxima. ICLR (2022)
Ziyin Liu, Botao Li, Xiangming Meng
Exact Solutions of a Deep Linear Network. NeurIPS (2022)
Ziyin Liu, Kentaro Minami, Kentaro Imajo
Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction. ICAIF (2022)
Zihao Wang, Ziyin Liu
Posterior Collapse of a Linear Latent Variable Model. CoRR (2022)
Ziyin Liu, Ekdeep Singh Lubana, Masahito Ueda, Hidenori Tanaka
What shapes the loss landscape of self-supervised learning? CoRR (2022)
Ziyin Liu, Zihao Wang
with a Simple Reparametrization. CoRR (2022)
Ziyin Liu, Masahito Ueda
Exact Phase Transitions in Deep Learning. CoRR (2022)
Takashi Mori, Ziyin Liu, Kangqiao Liu, Masahito Ueda
Power-Law Escape Rate of SGD. ICML (2022)
Ziyin Liu, Hanlin Zhang, Xiangming Meng, Yuting Lu, Eric P. Xing, Masahito Ueda
Stochastic Neural Networks with Infinite Width are Deterministic. CoRR (2022)
Zhiyi Zhang, Ziyin Liu
On the distributional properties of adaptive gradients. UAI (2021)
Kangqiao Liu, Ziyin Liu, Masahito Ueda
Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent. ICML (2021)
Ziyin Liu, Botao Li, Masahito Ueda
SGD May Never Escape Saddle Points. CoRR (2021)
Ziyin Liu, Kentaro Minami, Kentaro Imajo
What Data Augmentation Do We Need for Deep-Learning-Based Finance? CoRR (2021)
Paul Pu Liang, Peter Wu, Ziyin Liu, Louis-Philippe Morency, Ruslan Salakhutdinov
Cross-Modal Generalization: Learning in Low Resource Modalities via Meta-Alignment. ACM Multimedia (2021)
Zhiyi Zhang, Ziyin Liu
On the Distributional Properties of Adaptive Gradients. CoRR (2021)
Ziyin Liu, Kangqiao Liu, Takashi Mori, Masahito Ueda
On Minibatch Noise: Discrete-Time SGD, Overparametrization, and Bayes. CoRR (2021)
Takashi Mori, Ziyin Liu, Kangqiao Liu, Masahito Ueda
Logarithmic landscape and power-law escape rate of SGD. CoRR (2021)
Kangqiao Liu, Ziyin Liu, Masahito Ueda
Stochastic Gradient Descent with Large Learning Rate. CoRR (2020)
Paul Pu Liang, Terrance Liu, Ziyin Liu, Ruslan Salakhutdinov, Louis-Philippe Morency
Think Locally, Act Globally: Federated Learning with Local and Global Representations. CoRR (2020)
Paul Pu Liang, Peter Wu, Ziyin Liu, Louis-Philippe Morency, Ruslan Salakhutdinov
Cross-Modal Generalization: Learning in Low Resource Modalities via Meta-Alignment. CoRR (2020)
Ziyin Liu, 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 (2020)
Ziyin Liu, Zhikang Wang, Masahito Ueda
LaProp: a Better Way to Combine Momentum with Adaptive Gradient. CoRR (2020)
Ziyin Liu, Tilman Hartwig, Masahito Ueda
Neural Networks Fail to Learn Periodic Functions and How to Fix It. NeurIPS (2020)
Ziyin Liu, Tilman Hartwig, Masahito Ueda
Neural Networks Fail to Learn Periodic Functions and How to Fix It. CoRR (2020)
Ziyin Liu, Zihao Wang, Makoto Yamada, Masahito Ueda
Volumization as a Natural Generalization of Weight Decay. CoRR (2020)
Blair Chen, Ziyin Liu, Zihao Wang, Paul Pu Liang
An Investigation of how Label Smoothing Affects Generalization. CoRR (2020)
Ziyin Liu, Zhikang Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, Masahito Ueda
Deep Gamblers: Learning to Abstain with Portfolio Theory. CoRR (2019)
Ziyin Liu, Zhikang Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, Masahito Ueda
Deep Gamblers: Learning to Abstain with Portfolio Theory. NeurIPS (2019)
Paul Pu Liang, Ziyin Liu, Amir Zadeh, Louis-Philippe Morency
Multimodal Language Analysis with Recurrent Multistage Fusion. CoRR (2018)
Yixiu Zhao, Ziyin Liu
BlockPuzzle - A Challenge in Physical Reasoning and Generalization for Robot Learning. CoRR (2018)
Paul Pu Liang, Ziyin Liu, Amir Zadeh, Louis-Philippe Morency
Multimodal Language Analysis with Recurrent Multistage Fusion. EMNLP (2018)