| 2025 | AISTATS | Locally Optimal Descent for Dynamic Stepsize Scheduling. | Gilad Yehudai, Alon Cohen, Amit Daniely, Yoel Drori, Tomer Koren, Mariano Schain |
| 2025 | COLT | Logarithmic Width Suffices for Robust Memorization. | Amitsour Egosi, Gilad Yehudai, Ohad Shamir |
| 2025 | ICLR | Quality over Quantity in Attention Layers: When Adding More Heads Hurts. | Noah Amsel, Gilad Yehudai, Joan Bruna |
| 2024 | ALT | RedEx: Beyond Fixed Representation Methods via Convex Optimization. | Amit Daniely, Mariano Schain, Gilad Yehudai |
| 2022 | COLT | Width is Less Important than Depth in ReLU Neural Networks. | Gal Vardi, Gilad Yehudai, Ohad Shamir |
| 2022 | ICLR | On the Optimal Memorization Power of ReLU Neural Networks. | Gal Vardi, Gilad Yehudai, Ohad Shamir |
| 2021 | COLT | The Connection Between Approximation, Depth Separation and Learnability in Neural Networks. | Eran Malach, Gilad Yehudai, Shai Shalev-Shwartz, Ohad Shamir |
| 2021 | COLT | The Effects of Mild Over-parameterization on the Optimization Landscape of Shallow ReLU Neural Networks. | Itay Safran, Gilad Yehudai, Ohad Shamir |
| 2021 | ICML | From Local Structures to Size Generalization in Graph Neural Networks. | Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron |
| 2020 | COLT | Learning a Single Neuron with Gradient Methods. | Gilad Yehudai, Ohad Shamir |
| 2020 | ICML | Proving the Lottery Ticket Hypothesis: Pruning is All You Need. | Eran Malach, Gilad Yehudai, Shai Shalev-Shwartz, Ohad Shamir |