Vardi, Gal

40 publications

COLT 2025 A Theory of Learning with Autoregressive Chain of Thought Nirmit Joshi, Gal Vardi, Adam Block, Surbhi Goel, Zhiyuan Li, Theodor Misiakiewicz, Nathan Srebro

NeurIPS 2025 Benign Overfitting in Single-Head Attention Roey Magen, Shuning Shang, Zhiwei Xu, Spencer Frei, Wei Hu, Gal Vardi

ICLR 2025 Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks Nikolaos Tsilivis, Gal Vardi, Julia Kempe

NeurIPS 2025 Temperature Is All You Need for Generalization in Langevin Dynamics and Other Markov Processes Itamar Harel, Yonathan Wolanowsky, Gal Vardi, Nathan Srebro, Daniel Soudry

ICLR 2025 Trained Transformer Classifiers Generalize and Exhibit Benign Overfitting In-Context Spencer Frei, Gal Vardi

NeurIPS 2025 Transformers Are Almost Optimal Metalearners for Linear Classification Roey Magen, Gal Vardi

ICLR 2024 An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression Lijia Zhou, James B Simon, Gal Vardi, Nathan Srebro

ICLR 2024 Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data Zhiwei Xu, Yutong Wang, Spencer Frei, Gal Vardi, Wei Hu

NeurIPSW 2024 Benign Overfitting in Single-Head Attention Roey Magen, Shuning Shang, Zhiwei Xu, Spencer Frei, Wei Hu, Gal Vardi

NeurIPSW 2024 Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks Nikolaos Tsilivis, Gal Vardi, Julia Kempe

ICMLW 2024 Grokking, Rank Minimization and Generalization in Deep Learning David Yunis, Kumar Kshitij Patel, Samuel Wheeler, Pedro Henrique Pamplona Savarese, Gal Vardi, Karen Livescu, Michael Maire, Matthew Walter

ICLR 2024 Noisy Interpolation Learning with Shallow Univariate ReLU Networks Nirmit Joshi, Gal Vardi, Nathan Srebro

NeurIPS 2024 Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality Marko Medvedev, Gal Vardi, Nathan Srebro

NeurIPS 2024 Provable Tempered Overfitting of Minimal Nets and Typical Nets Itamar Harel, William M. Hoza, Gal Vardi, Itay Evron, Nathan Srebro, Daniel Soudry

ICMLW 2024 Provable Tempered Overfitting of Minimal Nets and Typical Nets Itamar Harel, William M. Hoza, Gal Vardi, Itay Evron, Nathan Srebro, Daniel Soudry

ICMLW 2024 Rank Minimization, Alignment and Weight Decay in Neural Networks David Yunis, Kumar Kshitij Patel, Samuel Wheeler, Pedro Henrique Pamplona Savarese, Gal Vardi, Karen Livescu, Michael Maire, Matthew Walter

NeurIPS 2023 Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces Odelia Melamed, Gilad Yehudai, Gal Vardi

NeurIPSW 2023 Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data Zhiwei Xu, Yutong Wang, Spencer Frei, Gal Vardi, Wei Hu

COLT 2023 Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization Spencer Frei, Gal Vardi, Peter Bartlett, Nathan Srebro

NeurIPS 2023 Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy Amit Daniely, Nati Srebro, Gal Vardi

NeurIPS 2023 Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi, Yakir Oz, Yaniv Nikankin, Michal Irani

ICLR 2023 Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data Spencer Frei, Gal Vardi, Peter Bartlett, Nathan Srebro, Wei Hu

ALT 2023 Implicit Regularization Towards Rank Minimization in ReLU Networks Nadav Timor, Gal Vardi, Ohad Shamir

NeurIPS 2023 Most Neural Networks Are Almost Learnable Amit Daniely, Nati Srebro, Gal Vardi

ICLRW 2023 Reconstructing Training Data from Multiclass Neural Networks Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi, Michal Irani

NeurIPS 2023 The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks Spencer Frei, Gal Vardi, Peter L. Bartlett, Nati Srebro

NeurIPS 2022 Gradient Methods Provably Converge to Non-Robust Networks Gal Vardi, Gilad Yehudai, Ohad Shamir

NeurIPSW 2022 On Convexity and Linear Mode Connectivity in Neural Networks David Yunis, Kumar Kshitij Patel, Pedro Henrique Pamplona Savarese, Gal Vardi, Jonathan Frankle, Matthew Walter, Karen Livescu, Michael Maire

NeurIPS 2022 On Margin Maximization in Linear and ReLU Networks Gal Vardi, Ohad Shamir, Nati Srebro

NeurIPS 2022 On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias Itay Safran, Gal Vardi, Jason Lee

ICLR 2022 On the Optimal Memorization Power of ReLU Neural Networks Gal Vardi, Gilad Yehudai, Ohad Shamir

NeurIPS 2022 Reconstructing Training Data from Trained Neural Networks Niv Haim, Gal Vardi, Gilad Yehudai, Ohad Shamir, Michal Irani

NeurIPS 2022 The Sample Complexity of One-Hidden-Layer Neural Networks Gal Vardi, Ohad Shamir, Nati Srebro

COLT 2022 Width Is Less Important than Depth in ReLU Neural Networks Gal Vardi, Gilad Yehudai, Ohad Shamir

COLT 2021 From Local Pseudorandom Generators to Hardness of Learning Amit Daniely, Gal Vardi

COLT 2021 Implicit Regularization in ReLU Networks with the Square Loss Gal Vardi, Ohad Shamir

NeurIPS 2021 Learning a Single Neuron with Bias Using Gradient Descent Gal Vardi, Gilad Yehudai, Ohad Shamir

COLT 2021 Size and Depth Separation in Approximating Benign Functions with Neural Networks Gal Vardi, Daniel Reichman, Toniann Pitassi, Ohad Shamir

NeurIPS 2020 Hardness of Learning Neural Networks with Natural Weights Amit Daniely, Gal Vardi

NeurIPS 2020 Neural Networks with Small Weights and Depth-Separation Barriers Gal Vardi, Ohad Shamir