Gilad Yehudai

Identifiers

• name variant Gilad Yehudai 0.60 · backfill

Papers (26)

1. Lost in Tokenization: Fundamental Trade-offs in Graph Tokenization for Transformers cs.LG · 2026 · author #2
2. Geometric Factual Recall in Transformers cs.CL · 2026 · author #2
3. Querying Kernel Methods Suffices for Reconstructing their Training Data cs.LG · 2025 · author #4
4. Depth-Width tradeoffs in Algorithmic Reasoning of Graph Tasks with Transformers cs.LG · 2025 · author #1
5. Logarithmic Width Suffices for Robust Memorization cs.LG · 2025 · author #2
6. On the Reconstruction of Training Data from Group Invariant Networks cs.LG · 2024 · author #2
7. On the Benefits of Rank in Attention Layers cs.LG · 2024 · author #2
8. Reconstructing Training Data From Real World Models Trained with Transfer Learning cs.LG · 2024 · author #2
9. MALT Powers Up Adversarial Attacks cs.LG · 2024 · author #2
10. RedEx: Beyond Fixed Representation Methods via Convex Optimization cs.LG · 2024 · author #3
11. Locally Optimal Descent for Dynamic Stepsize Scheduling cs.LG · 2023 · author #1
12. Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses cs.LG · 2023 · author #3
13. From Tempered to Benign Overfitting in ReLU Neural Networks cs.LG · 2023 · author #2
14. Reconstructing Training Data from Multiclass Neural Networks cs.LG · 2023 · author #3
15. Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces cs.LG · 2023 · author #2
16. Reconstructing Training Data from Trained Neural Networks cs.LG · 2022 · author #3
17. Gradient Methods Provably Converge to Non-Robust Networks cs.LG · 2022 · author #2
18. Width is Less Important than Depth in ReLU Neural Networks cs.LG · 2022 · author #2
19. On the Optimal Memorization Power of ReLU Neural Networks cs.LG · 2021 · author #2
20. Learning a Single Neuron with Bias Using Gradient Descent cs.LG · 2021 · author #2
21. The Connection Between Approximation, Depth Separation and Learnability in Neural Networks cs.LG · 2021 · author #2
22. From Local Structures to Size Generalization in Graph Neural Networks cs.LG · 2020 · author #1
23. The Effects of Mild Over-parameterization on the Optimization Landscape of Shallow ReLU Neural Networks cs.LG · 2020 · author #2
24. Proving the Lottery Ticket Hypothesis: Pruning is All You Need cs.LG · 2020 · author #2
25. Learning a Single Neuron with Gradient Methods cs.LG · 2020 · author #1
26. On the Power and Limitations of Random Features for Understanding Neural Networks cs.LG · 2019 · author #1

Mentions

• 2505.19019 #4 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2502.11162 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2411.16458 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2407.16153 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2407.15845 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2407.02240 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2305.15141 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2401.07606 #3 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2311.13877 #1 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2303.00783 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2307.01827 #3 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2305.03350 #3 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2206.07758 #3 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2202.04347 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2202.03841 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2001.05205 #1 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 1904.00687 #1 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2106.01101 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2110.03187 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2006.01005 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2102.00434 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2010.08853 #1 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2002.00585 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2503.01805 #1 · arxiv_oai · confidence 0.70 Gilad Yehudai
• 2605.22471 #2 · arxiv_oai · confidence 0.70 Gilad Yehudai

Frequent Coauthors

• Ohad Shamir 12 shared papers
• Gal Vardi 9 shared papers
• Michal Irani 4 shared papers
• Niv Haim 4 shared papers
• Joan Bruna 3 shared papers
• Amir Globerson 2 shared papers
• Amit Daniely 2 shared papers
• Clayton Sanford 2 shared papers
• Eran Malach 2 shared papers
• Gon Buzaglo 2 shared papers
• Haggai Maron 2 shared papers
• Mariano Schain 2 shared papers
• Maya Bechler-Speicher 2 shared papers
• Meirav Galun 2 shared papers
• Odelia Melamed 2 shared papers
• Shai Shalev-Shwartz 2 shared papers
• Yakir Oz 2 shared papers
• Adi Shamir 1 shared papers
• Alberto Bietti 1 shared papers
• Alon Cohen 1 shared papers