Clustering with Bregman Divergences: an Asymptotic Analysis. - Chaoyue Liu 001; Mikhail Belkin (NIPS, 2016)

Parametrized Accelerated Methods Free of Condition Number. - Chaoyue Liu 001; Mikhail Belkin (CoRR, 2018)

MaSS: an Accelerated Stochastic Method for Over-parametrized Learning. - Chaoyue Liu 001; Mikhail Belkin (CoRR, 2018)

OTDA: a Unsupervised Optimal Transport framework with Discriminant Analysis for Keystroke Inference. - Kun Jin; Chaoyue Liu 001; Cathy Xia (CNS, 2020)

Accelerating SGD with momentum for over-parameterized learning. - Chaoyue Liu 001; Mikhail Belkin (ICLR, 2020)

On the linearity of large non-linear models: when and why the tangent kernel is constant. - Chaoyue Liu 001; Libin Zhu; Mikhail Belkin (NeurIPS, 2020)

Toward a theory of optimization for over-parameterized systems of non-linear equations: the lessons of deep learning. - Chaoyue Liu 001; Libin Zhu; Mikhail Belkin (CoRR, 2020)

Two-Sided Wasserstein Procrustes Analysis. - Kun Jin; Chaoyue Liu 001; Cathy Xia (IJCAI, 2021)

Transition to Linearity of Wide Neural Networks is an Emerging Property of Assembling Weak Models. - Chaoyue Liu 001; Libin Zhu; Mikhail Belkin (ICLR, 2022)

Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture. - Libin Zhu; Chaoyue Liu 001; Mikhail Belkin (NeurIPS, 2022)

Quadratic models for understanding neural network dynamics. - Libin Zhu; Chaoyue Liu 001; Adityanarayanan Radhakrishnan; Mikhail Belkin (CoRR, 2022)

Aiming towards the minimizers: fast convergence of SGD for overparametrized problems. - Chaoyue Liu 001; Dmitriy Drusvyatskiy; Mikhail Belkin; Damek Davis; Yi-An Ma (NeurIPS, 2023)

On Emergence of Clean-Priority Learning in Early Stopped Neural Networks. - Chaoyue Liu 001; Amirhesam Abedsoltan; Mikhail Belkin (CoRR, 2023)

Quadratic models for understanding catapult dynamics of neural networks. - Libin Zhu; Chaoyue Liu 001; Adityanarayanan Radhakrishnan; Mikhail Belkin (ICLR, 2024)

Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning. - Libin Zhu; Chaoyue Liu 001; Adityanarayanan Radhakrishnan; Mikhail Belkin (ICML, 2024)