|
Poster
|
|
Implicit Regularization for Group Sparsity
Jiangyuan Li · THANH NGUYEN · Chinmay Hegde · Raymond K. W. Wong
|
|
|
Poster
|
|
Approximate Bayesian Inference with Stein Functional Variational Gradient Descent
Tobias Pielok · Bernd Bischl · David Rügamer
|
|
|
Poster
|
Wed 2:30
|
Implicit regularization in Heavy-ball momentum accelerated stochastic gradient descent
Avrajit Ghosh · HE LYU · Xitong Zhang · Rongrong Wang
|
|
|
Oral
|
Wed 1:30
|
Implicit regularization in Heavy-ball momentum accelerated stochastic gradient descent
Avrajit Ghosh · HE LYU · Xitong Zhang · Rongrong Wang
|
|
|
Poster
|
|
Projective Proximal Gradient Descent for Nonconvex Nonsmooth Optimization: Fast Convergence Without Kurdyka-Lojasiewicz (KL) Property
Yingzhen Yang · Ping Li
|
|
|
Workshop
|
Thu 4:00
|
Why Can GPT Learn In-Context? Language Models Implicitly Perform Gradient Descent as Meta-Optimizers
Damai Dai · Yutao Sun · Li Dong · Yaru Hao · Shuming Ma · Zhifang Sui · Furu Wei
|
|
|
Oral
|
Wed 1:50
|
Learning with Logical Constraints but without Shortcut Satisfaction
Zenan Li · Zehua Liu · Yuan Yao · Jingwei Xu · Taolue Chen · Xiaoxing Ma · Jian Lu
|
|
|
Poster
|
|
Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition
Jianhao Ma · Lingjun Guo · Salar Fattahi
|
|
|
Poster
|
Wed 2:30
|
Learning with Logical Constraints but without Shortcut Satisfaction
Zenan Li · Zehua Liu · Yuan Yao · Jingwei Xu · Taolue Chen · Xiaoxing Ma · Jian Lu
|
|
|
Poster
|
Mon 2:30
|
How gradient estimator variance and bias impact learning in neural networks
Arna Ghosh · Yuhan Helena Liu · Guillaume Lajoie · Konrad P Kording · Blake A Richards
|
|
|
Poster
|
|
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization
Difan Zou · Yuan Cao · Yuanzhi Li · Quanquan Gu
|
|
|
Poster
|
Wed 2:30
|
Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability
Alex Damian · Eshaan Nichani · Jason Lee
|
|
