Chaoyue Liu
9 papers · 2016–2024 · 4 venues · across top CS/AI venues
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Achievements
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🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (15) 🐣 Hot Topic Early Bird
🔥
Unstoppable · Bronze
Venues
Top co-authors
Research topics
Keywords
neural tangent kernel
(3)
neural network
(3)
neural network optimization
(3)
transition to linearity
(2)
convergence rate
(2)
gradient descent
(2)
stochastic gradient descent
(2)
deep learning
(1)
tangent kernels
(1)
asymptotic analysis
(1)
procrustes analysis
(1)
bregman divergence
(1)
quadratic models
(1)
hessian matrix
(1)
overparameterized model
(1)
directed acyclic graph
(1)
batch size
(1)
interpolation regime
(1)
infinite width
(1)
overparameterized learning
(1)
Papers
Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning
ICML 2024
Quadratic models for understanding catapult dynamics of neural networks
ICLR 2024
Aiming towards the minimizers: fast convergence of SGD for overparametrized problems
NeurIPS 2023
Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture
NeurIPS 2022
Transition to Linearity of Wide Neural Networks is an Emerging Property of Assembling Weak Models
ICLR 2022
Two-Sided Wasserstein Procrustes Analysis
IJCAI 2021
Accelerating SGD with momentum for over-parameterized learning
ICLR 2020
On the linearity of large non-linear models: when and why the tangent kernel is constant
NeurIPS 2020
Clustering with Bregman Divergences: an Asymptotic Analysis
NeurIPS 2016