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Poster
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Thu 14:00
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Integral Probability Metrics PAC-Bayes Bounds
Ron Amit · Baruch Epstein · Shay Moran · Ron Meir
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Poster
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Tue 14:00
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Differentially Private Learning with Margin Guarantees
Raef Bassily · Mehryar Mohri · Ananda Theertha Suresh
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Poster
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Wed 9:00
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Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime
Difan Zou · Jingfeng Wu · Vladimir Braverman · Quanquan Gu · Sham Kakade
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Poster
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Tue 9:00
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On the Importance of Gradient Norm in PAC-Bayesian Bounds
Itai Gat · Yossi Adi · Alex Schwing · Tamir Hazan
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Poster
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Thu 14:00
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Benign Underfitting of Stochastic Gradient Descent
Tomer Koren · Roi Livni · Yishay Mansour · Uri Sherman
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Poster
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Thu 9:00
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Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers
Colin Wei · Yining Chen · Tengyu Ma
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Poster
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Generalization Bounds for Gradient Methods via Discrete and Continuous Prior
Xuanyuan Luo · Bei Luo · Jian Li
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Poster
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Wed 9:00
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Generalization Bounds for Stochastic Gradient Descent via Localized ε-Covers
Sejun Park · Umut Simsekli · Murat Erdogdu
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Poster
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Wed 9:00
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Stability Analysis and Generalization Bounds of Adversarial Training
Jiancong Xiao · Yanbo Fan · Ruoyu Sun · Jue Wang · Zhi-Quan Luo
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Poster
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Tue 9:00
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Generalization Error Bounds on Deep Learning with Markov Datasets
Lan V. Truong
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Poster
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Thu 14:00
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A PAC-Bayesian Generalization Bound for Equivariant Networks
Arash Behboodi · Gabriele Cesa · Taco Cohen
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Poster
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Fine-Grained Analysis of Stability and Generalization for Modern Meta Learning Algorithms
Jiechao Guan · Yong Liu · Zhiwu Lu
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