Chaoyue Liu

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 19

Top Topics

Bregman Divergences

Directed Acyclic Graph

Top Venues

Publications

Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Mikhail Belkin
Quadratic models for understanding catapult dynamics of neural networks. ICLR (2024)
Chaoyue Liu, Amirhesam Abedsoltan, Mikhail Belkin
On Emergence of Clean-Priority Learning in Early Stopped Neural Networks. CoRR (2023)
Chaoyue Liu, Dmitriy Drusvyatskiy, Misha Belkin, Damek Davis, Yi-An Ma
Aiming towards the minimizers: fast convergence of SGD for overparametrized problems. NeurIPS (2023)
Chaoyue Liu, Dmitriy Drusvyatskiy, Mikhail Belkin, Damek Davis, Yi-An Ma
Aiming towards the minimizers: fast convergence of SGD for overparametrized problems. CoRR (2023)
Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Mikhail Belkin
Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning. CoRR (2023)
Chaoyue Liu, Libin Zhu, Misha Belkin
Transition to Linearity of Wide Neural Networks is an Emerging Property of Assembling Weak Models. ICLR (2022)
Libin Zhu, Chaoyue Liu, Mikhail Belkin
Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture. CoRR (2022)
Chaoyue Liu, Libin Zhu, Mikhail Belkin
Transition to Linearity of Wide Neural Networks is an Emerging Property of Assembling Weak Models. CoRR (2022)
Libin Zhu, Chaoyue Liu, Misha Belkin
Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture. NeurIPS (2022)
Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Mikhail Belkin
Quadratic models for understanding neural network dynamics. CoRR (2022)
Kun Jin, Chaoyue Liu, Cathy Xia
Two-Sided Wasserstein Procrustes Analysis. IJCAI (2021)
Kun Jin, Chaoyue Liu, Cathy Xia
OTDA: a Unsupervised Optimal Transport framework with Discriminant Analysis for Keystroke Inference. CNS (2020)
Chaoyue Liu, Libin Zhu, Mikhail Belkin
On the linearity of large non-linear models: when and why the tangent kernel is constant. CoRR (2020)
Chaoyue Liu, Libin Zhu, Mikhail Belkin
Toward a theory of optimization for over-parameterized systems of non-linear equations: the lessons of deep learning. CoRR (2020)
Chaoyue Liu, Libin Zhu, Mikhail Belkin
On the linearity of large non-linear models: when and why the tangent kernel is constant. NeurIPS (2020)
Chaoyue Liu, Mikhail Belkin
Accelerating SGD with momentum for over-parameterized learning. ICLR (2020)
Chaoyue Liu, Mikhail Belkin
Parametrized Accelerated Methods Free of Condition Number. CoRR (2018)
Chaoyue Liu, Mikhail Belkin
MaSS: an Accelerated Stochastic Method for Over-parametrized Learning. CoRR (2018)
Chaoyue Liu, Mikhail Belkin
Clustering with Bregman Divergences: an Asymptotic Analysis. NIPS (2016)