Chaoyue Liu - RankMe

20 papers A* 8Journal 10Unranked 2

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