Gilad Yehudai

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 36

Top Topics

Dimensional Data

Linear Subspace

Top Venues

Publications

Amit Daniely, Mariano Schain, Gilad Yehudai
RedEx: Beyond Fixed Representation Methods via Convex Optimization. ALT (2024)
Amit Daniely, Mariano Schain, Gilad Yehudai
RedEx: Beyond Fixed Representation Methods via Convex Optimization. CoRR (2024)
Gilad Yehudai, Haim Kaplan, Asma Ghandeharioun, Mor Geva, Amir Globerson
When Can Transformers Count to n? CoRR (2024)
Noah Amsel, Gilad Yehudai, Joan Bruna
On the Benefits of Rank in Attention Layers. CoRR (2024)
Yakir Oz, Gilad Yehudai, Gal Vardi, Itai Antebi, Michal Irani, Niv Haim
Reconstructing Training Data From Real World Models Trained with Transfer Learning. CoRR (2024)
Odelia Melamed, Gilad Yehudai, Adi Shamir
MALT Powers Up Adversarial Attacks. CoRR (2024)
Guy Kornowski, Gilad Yehudai, Ohad Shamir
From Tempered to Benign Overfitting in ReLU Neural Networks. CoRR (2023)
Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi, Yakir Oz, Yaniv Nikankin, Michal Irani
Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses. NeurIPS (2023)
Gilad Yehudai, Alon Cohen, Amit Daniely, Yoel Drori, Tomer Koren, Mariano Schain
Locally Optimal Descent for Dynamic Stepsize Scheduling. CoRR (2023)
Odelia Melamed, Gilad Yehudai, Gal Vardi
Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces. NeurIPS (2023)
Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi, Michal Irani
Reconstructing Training Data from Multiclass Neural Networks. CoRR (2023)
Odelia Melamed, Gilad Yehudai, Gal Vardi
Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Data Manifolds. CoRR (2023)
Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi, Yakir Oz, Yaniv Nikankin, Michal Irani
Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses. CoRR (2023)
Guy Kornowski, Gilad Yehudai, Ohad Shamir
From Tempered to Benign Overfitting in ReLU Neural Networks. NeurIPS (2023)
Gal Vardi, Gilad Yehudai, Ohad Shamir
On the Optimal Memorization Power of ReLU Neural Networks. ICLR (2022)
Gal Vardi, Gilad Yehudai, Ohad Shamir
Gradient Methods Provably Converge to Non-Robust Networks. NeurIPS (2022)
Gal Vardi, Gilad Yehudai, Ohad Shamir
Gradient Methods Provably Converge to Non-Robust Networks. CoRR (2022)
Niv Haim, Gal Vardi, Gilad Yehudai, Ohad Shamir, Michal Irani
Reconstructing Training Data from Trained Neural Networks. CoRR (2022)
Gal Vardi, Gilad Yehudai, Ohad Shamir
Width is Less Important than Depth in ReLU Neural Networks. CoRR (2022)
Gal Vardi, Gilad Yehudai, Ohad Shamir
Width is Less Important than Depth in ReLU Neural Networks. COLT (2022)
Niv Haim, Gal Vardi, Gilad Yehudai, Ohad Shamir, Michal Irani
Reconstructing Training Data From Trained Neural Networks. NeurIPS (2022)
Eran Malach, Gilad Yehudai, Shai Shalev-Shwartz, Ohad Shamir
The Connection Between Approximation, Depth Separation and Learnability in Neural Networks. COLT (2021)
Gal Vardi, Gilad Yehudai, Ohad Shamir
Learning a Single Neuron with Bias Using Gradient Descent. CoRR (2021)
Eran Malach, Gilad Yehudai, Shai Shalev-Shwartz, Ohad Shamir
The Connection Between Approximation, Depth Separation and Learnability in Neural Networks. CoRR (2021)
Gal Vardi, Gilad Yehudai, Ohad Shamir
Learning a Single Neuron with Bias Using Gradient Descent. NeurIPS (2021)
Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron
From Local Structures to Size Generalization in Graph Neural Networks. ICML (2021)
Itay M. Safran, Gilad Yehudai, Ohad Shamir
The Effects of Mild Over-parameterization on the Optimization Landscape of Shallow ReLU Neural Networks. COLT (2021)
Gal Vardi, Gilad Yehudai, Ohad Shamir
On the Optimal Memorization Power of ReLU Neural Networks. CoRR (2021)
Gilad Yehudai, Ohad Shamir
Learning a Single Neuron with Gradient Methods. COLT (2020)
Eran Malach, Gilad Yehudai, Shai Shalev-Shwartz, Ohad Shamir
Proving the Lottery Ticket Hypothesis: Pruning is All You Need. CoRR (2020)
Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron
On Size Generalization in Graph Neural Networks. CoRR (2020)
Itay Safran, Gilad Yehudai, Ohad Shamir
The Effects of Mild Over-parameterization on the Optimization Landscape of Shallow ReLU Neural Networks. CoRR (2020)
Gilad Yehudai, Ohad Shamir
Learning a Single Neuron with Gradient Methods. CoRR (2020)
Eran Malach, Gilad Yehudai, Shai Shalev-Shwartz, Ohad Shamir
Proving the Lottery Ticket Hypothesis: Pruning is All You Need. ICML (2020)
Gilad Yehudai, Ohad Shamir
On the Power and Limitations of Random Features for Understanding Neural Networks. NeurIPS (2019)
Gilad Yehudai, Ohad Shamir
On the Power and Limitations of Random Features for Understanding Neural Networks. CoRR (2019)