Skip to main content
An official website of the European UnionAn official EU website
European Commission logo
English English
CORDIS - EU research results
CORDIS
CORDIS Web 30th anniversary CORDIS Web 30th anniversary

A Theory for Understanding, Designing, and Training Deep Learning Systems

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Neural Networks with Small Weights and Depth-Separation Barriers

Author(s): Gal Vardi and Ohad Shamir
Published in: 2020
Publisher: NeurIPS 2020

On Margin Maximization in Linear and ReLU Networks

Author(s): Gal Vardi, Gilad Yehudai, Ohad Shamir
Published in: 36th Conference on Neural Information Processing Systems (NeurIPS 2022), Issue 36, 2022
Publisher: NeurIPS

Initialization-dependent sample complexity of linear predictors and neural networks

Author(s): R Magen, O Shamir
Published in: 2023
Publisher: Advances in Neural Information Processing Systems

Implicit Regularization Towards Rank Minimization in ReLU Networks

Author(s): Nadav Timor, Gal Vardi and Ohad Shamir
Published in: 2023
Publisher: ALT

The Sample Complexity of One-Hidden-Layer Neural Networks

Author(s): Gal Vardi, Ohad Shamir and Nathan Srebro
Published in: 2022
Publisher: NeurIPS

Learning a Single Neuron with Bias Using Gradient Descent

Author(s): Gal Vardi, Gilad Yehudai, Ohad Shamir
Published in: 2021
Publisher: NeurIP

Deterministic nonsmooth nonconvex optimization

Author(s): M Jordan, G Kornowski, T Lin, O Shamir, M Zampetakis
Published in: 2023
Publisher: Proceedings of COLT 2023

Width is Less Important than Depth in ReLU Neural Networks

Author(s): Gal Vardi, Gilad Yehudai and Ohad Shamir
Published in: 2022
Publisher: COLT

Open Problem: Anytime Convergence Rate of Gradient Descent

Author(s): G Kornowski, O Shamir
Published in: 2024
Publisher: Proceedings of COLT 2024

Gradient Methods Provably Converge to Non-Robust Networks

Author(s): Gal Vardi, Gilad Yehudai and Ohad Shamir
Published in: 2022
Publisher: NeurIPS

Reconstructing Training Data from Trained Neural Networks

Author(s): Niv Haim, Gal Vardi, Gilad Yehudai, Ohad Shamir, Michal Irani
Published in: 2022
Publisher: NeurIPS

The Connection Between Approximation, Depth Separation and Learnability in Neural Networks

Author(s): Eran Malach, Gilad Yehudai, Shai Shalev-Shwartz, Ohad Shamir
Published in: 2021
Publisher: COLT 2021

The Effects of Mild Over-parameterization on the Optimization Landscapeof Shallow ReLU Neural Networks

Author(s): Itay Safran, Gilad Yehudai and Ohad Shamir
Published in: 2021
Publisher: COLT 2021

Implicit Regularization in ReLU Networks with the Square Loss

Author(s): Gal Vardi and Ohad Shamir
Published in: 2021
Publisher: COLT 2021

Oracle Complexity in Nonsmooth Nonconvex Optimization

Author(s): Guy Kornowski and Ohad Shamir
Published in: 2021
Publisher: NeurIPS

Depth Separation in Norm-Bounded Infinite-Width Neural Networks

Author(s): S Parkinson, G Ongie, R Willett, O Shamir, N Srebro
Published in: 2024
Publisher: Proceedings of COLT 2024

The Implicit Bias of Benign Overfitting

Author(s): Ohad Shamir
Published in: 2022
Publisher: COLT

Are ResNets Provably Better than Linear Predictors?

Author(s): Ohad Shamir
Published in: 2018
Publisher: NeurIPS conference

On the Power and Limitations of Random Features for Understanding Neural Networks

Author(s): Gilad Yehudai and Ohad Shamir
Published in: 2019
Publisher: NeurIPS conference

Exponential Convergence Time of Gradient Descent for One-Dimensional Deep Linear Neural Networks

Author(s): Ohad Shamir
Published in: 2019
Publisher: COLT conference

Depth Separations in Neural Networks: What is Actually Being Separated?

Author(s): Itay Safran, Ronen Eldan, Ohad Shamir
Published in: 2019
Publisher: COLT conference

The Complexity of Making the Gradient Small in Stochastic Convex Optimization

Author(s): Dylan Foster, Ayush Sekhari, Ohad Shamir, Nathan Srebro, Karthik Sridharan, Blake Woodworth
Published in: 2019
Publisher: COLT conference

Learning a Single Neuron with Gradient Methods

Author(s): Gilad Yehudai and Ohad Shamir
Published in: 2020
Publisher: COLT 2020

How Good is SGD with Random Shuffling?

Author(s): Itay Safran and Ohad Shamir
Published in: 2020
Publisher: COLT 2020

Proving the Lottery Ticket Hypothesis: Pruning is All You Need

Author(s): Eran Malach, Gilad Yehudai, Shai Shalev-Shwartz, Ohad Shamir
Published in: 2020
Publisher: ICML 2020

From tempered to benign overfitting in relu neural networks

Author(s): Guy Kornowski, Gilad Yehudai, Ohad Shamir
Published in: 2023
Publisher: Advances in Neural Information Processing Systems

Random Shuffling Beats SGD Only After Many Epochs on Ill-Conditioned Problems

Author(s): Itay Safran and Ohad Shamir
Published in: 2021
Publisher: NeurIPS

On the Optimal Memorization Power of ReLU Neural Networks

Author(s): Gal Vardi, Gilad Yehudai, Ohad Shamir
Published in: The Optimal Memorization Power of ReLU Neural Networks ICLR 2022, 2022
Publisher: ICLR

Size and Depth Separation in Approximating Natural Functions with Neural Networks

Author(s): Gal Vardi, Daniel Reichman, Toniann Pitassi, Ohad Shamir
Published in: 2021
Publisher: COLT 2021

Generalization in kernel regression under realistic assumptions

Author(s): Daniel Barzilai, Ohad Shamir
Published in: 2024
Publisher: Proceedings of ICML 2024

Gradient Methods Never Overfit On Separable Data

Author(s): Ohad Shamir
Published in: Journal of Machine Learning Research, 2020, ISSN 1533-7928
Publisher: None (independent electronic journal)

An algorithm with optimal dimension-dependence for zero-order nonsmooth nonconvex stochastic optimization

Author(s): G Kornowski, O Shamir
Published in: Journal of Machine Learning Research, 2024, ISSN 1533-7928
Publisher: Journal of Machine Learning Research

Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Data Manifolds

Author(s): Odelia Melamed, Gilad Yehudai, Gal Vardi
Published in: 2023
Publisher: arXiv

Can We Find Near-Approximately-Stationary Points of Nonsmooth Nonconvex Functions?

Author(s): Ohad Shamir
Published in: 2020
Publisher: arXiv preprint

On the Complexity of Finding Small Subgradients in Nonsmooth Optimization

Author(s): Guy Kornowski and Ohad Shamir
Published in: 2022
Publisher: arXiv

There was an error trying to search data from OpenAIRE

No results available