Poster

Mon 17:00

Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry
Ziyi Chen · Yi Zhou · Tengyu Xu · Yingbin Liang

Poster

Tue 17:00

Understanding the role of importance weighting for deep learning
Da Xu · Yuting Ye · Chuanwei Ruan

Spotlight

Wed 20:20

Understanding the role of importance weighting for deep learning
Da Xu · Yuting Ye · Chuanwei Ruan

Oral

Thu 0:30

Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime
Atsushi Nitanda · Taiji Suzuki

Poster

Thu 1:00

Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime
Atsushi Nitanda · Taiji Suzuki

Poster

Thu 9:00

Linear Last-iterate Convergence in Constrained Saddle-point Optimization
Chen-Yu Wei · Chung-Wei Lee · Mengxiao Zhang · Haipeng Luo

Poster

Tue 17:00

Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability
Jeremy Cohen · Simran Kaur · Yuanzhi Li · Zico Kolter · Ameet Talwalkar

Poster

Thu 1:00

The inductive bias of ReLU networks on orthogonally separable data
Mary Phuong · Christoph H Lampert

Poster

Mon 9:00

On the Impossibility of Global Convergence in Multi-Loss Optimization
Alistair Letcher

Poster

Tue 9:00

Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate
Jingfeng Wu · Difan Zou · vladimir braverman · Quanquan Gu

Poster

Tue 9:00

On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers
Kenji Kawaguchi

Poster

Tue 9:00

Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning
Zhiyuan Li · Yuping Luo · Kaifeng Lyu