Poster

Thu 14:00

Integral Probability Metrics PAC-Bayes Bounds
Ron Amit · Baruch Epstein · Shay Moran · Ron Meir

Poster

Tue 14:00

Differentially Private Learning with Margin Guarantees
Raef Bassily · Mehryar Mohri · Ananda Theertha Suresh

Poster

Wed 9:00

Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime
Difan Zou · Jingfeng Wu · Vladimir Braverman · Quanquan Gu · Sham Kakade

Poster

Thu 14:00

Benign Underfitting of Stochastic Gradient Descent
Tomer Koren · Roi Livni · Yishay Mansour · Uri Sherman

Poster

Tue 9:00

On the Importance of Gradient Norm in PAC-Bayesian Bounds
Itai Gat · Yossi Adi · Alex Schwing · Tamir Hazan

Poster

Wed 9:00

Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$-Covers
Sejun Park · Umut Simsekli · Murat Erdogdu

Poster

Thu 9:00

Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers
Colin Wei · Yining Chen · Tengyu Ma

Poster

Generalization Bounds for Gradient Methods via Discrete and Continuous Prior
Xuanyuan Luo · Bei Luo · Jian Li

Poster

Wed 9:00

Stability Analysis and Generalization Bounds of Adversarial Training
Jiancong Xiao · Yanbo Fan · Ruoyu Sun · Jue Wang · Zhi-Quan Luo

Poster

Thu 14:00

A PAC-Bayesian Generalization Bound for Equivariant Networks
Arash Behboodi · Gabriele Cesa · Taco Cohen

Poster

Tue 9:00

Generalization Error Bounds on Deep Learning with Markov Datasets
Lan V. Truong

Poster

Fine-Grained Analysis of Stability and Generalization for Modern Meta Learning Algorithms
Jiechao Guan · Yong Liu · Zhiwu Lu