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Chaoyue Liu 0001
Person information
- affiliation: Ohio State University, Department of Computer Science and Engineering, Columbus, OH, USA
Other persons with the same name
- Chaoyue Liu 0002 — Huazhong University of Science and Technology, School of Electronic Information and Communications, Wuhan, China
- Chaoyue Liu 0003 — Beijing Institute of Technology, MoE Key Laboratory of Dynamics and Control of Flight Vehicle, China
- Chaoyue Liu 0004 — Shenzhen Mindray Bio-Medical Electronics, Co., Ltd., China
- Chaoyue Liu 0005 — Guizhou Traffic Planning, Survey and Design Institute Co., Ltd., Guiyang, China
- Chaoyue Liu 0006 — Zhejiang University of Science and Technology, School of Information Technology and Electronics Engineering, Hangzhou, China
- Chaoyue Liu 0007 — North China University of Science and Technology, Tangshan, China
- Chaoyue Liu 0008 — Beijing University of Posts and Telecommunications, Key Laboratory of Universal Wireless Communications, China
- Chaoyue Liu 0009 — Zhengzhou University, School of Computer and Artificial Intelligence, China
- Chaoyue Liu 0010 — University of California San Diego, HDSI, CA, USA
- Chaoyue Liu 0011 — Université de Picardie Jules Verne, Amiens, France
- Chaoyue Liu 0012 — Chinese Academy of Sciences, Aerospace Information Research Institute, Department of Space Microwave Remote Sensing System, Beijing, China (and 1 more)
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2020 – today
- 2024
- [c10]Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Mikhail Belkin:
Quadratic models for understanding catapult dynamics of neural networks. ICLR 2024 - [c9]Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Mikhail Belkin:
Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning. ICML 2024 - 2023
- [c8]Chaoyue Liu, Dmitriy Drusvyatskiy, Misha Belkin, Damek Davis, Yi-An Ma:
Aiming towards the minimizers: fast convergence of SGD for overparametrized problems. NeurIPS 2023 - [i10]Chaoyue Liu, Amirhesam Abedsoltan, Mikhail Belkin:
On Emergence of Clean-Priority Learning in Early Stopped Neural Networks. CoRR abs/2306.02533 (2023) - [i9]Chaoyue Liu, Dmitriy Drusvyatskiy, Mikhail Belkin, Damek Davis, Yi-An Ma:
Aiming towards the minimizers: fast convergence of SGD for overparametrized problems. CoRR abs/2306.02601 (2023) - [i8]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 abs/2306.04815 (2023) - 2022
- [c7]Chaoyue Liu, Libin Zhu, Misha Belkin:
Transition to Linearity of Wide Neural Networks is an Emerging Property of Assembling Weak Models. ICLR 2022 - [c6]Libin Zhu, Chaoyue Liu, Misha Belkin:
Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture. NeurIPS 2022 - [i7]Chaoyue Liu, Libin Zhu, Mikhail Belkin:
Transition to Linearity of Wide Neural Networks is an Emerging Property of Assembling Weak Models. CoRR abs/2203.05104 (2022) - [i6]Libin Zhu, Chaoyue Liu, Mikhail Belkin:
Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture. CoRR abs/2205.11786 (2022) - [i5]Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Mikhail Belkin:
Quadratic models for understanding neural network dynamics. CoRR abs/2205.11787 (2022) - 2021
- [c5]Kun Jin, Chaoyue Liu, Cathy Xia:
Two-Sided Wasserstein Procrustes Analysis. IJCAI 2021: 3515-3521 - 2020
- [c4]Kun Jin, Chaoyue Liu, Cathy Xia:
OTDA: a Unsupervised Optimal Transport framework with Discriminant Analysis for Keystroke Inference. CNS 2020: 1-9 - [c3]Chaoyue Liu, Mikhail Belkin:
Accelerating SGD with momentum for over-parameterized learning. ICLR 2020 - [c2]Chaoyue Liu, Libin Zhu, Mikhail Belkin:
On the linearity of large non-linear models: when and why the tangent kernel is constant. NeurIPS 2020 - [i4]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 abs/2003.00307 (2020) - [i3]Chaoyue Liu, Libin Zhu, Mikhail Belkin:
On the linearity of large non-linear models: when and why the tangent kernel is constant. CoRR abs/2010.01092 (2020)
2010 – 2019
- 2018
- [i2]Chaoyue Liu, Mikhail Belkin:
Parametrized Accelerated Methods Free of Condition Number. CoRR abs/1802.10235 (2018) - [i1]Chaoyue Liu, Mikhail Belkin:
MaSS: an Accelerated Stochastic Method for Over-parametrized Learning. CoRR abs/1810.13395 (2018) - 2016
- [c1]Chaoyue Liu, Mikhail Belkin:
Clustering with Bregman Divergences: an Asymptotic Analysis. NIPS 2016: 2343-2351
Coauthor Index
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