Gal Vardi - RankMe

88 papers A* 30A 1B 5Journal 50Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Positive Distribution Shift as a Framework for Understanding Tractable Learning. CoRR Marko Medvedev, Idan Attias, Elisabetta Cornacchia, Theodor Misiakiewicz, Gal Vardi, Nathan Srebro
2026	J	`jnl`	The Implicit Bias of Adam and Muon on Smooth Homogeneous Neural Networks. CoRR Eitan Gronich, Gal Vardi
2026	J	`jnl`	To Grok Grokking: Provable Grokking in Ridge Regression. CoRR Mingyue Xu, Gal Vardi, Itay Safran
2025	A*	`conf`	A Theory of Learning with Autoregressive Chain of Thought. COLT Nirmit Joshi, Gal Vardi, Adam Block, Surbhi Goel, Zhiyuan Li, Theodor Misiakiewicz, Nathan Srebro
2025	J	`jnl`	A Theory of Learning with Autoregressive Chain of Thought. CoRR Nirmit Joshi, Gal Vardi, Adam Block, Surbhi Goel, Zhiyuan Li, Theodor Misiakiewicz, Nathan Srebro
2025	A*	`conf`	Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks. ICLR Nikolaos Tsilivis, Gal Vardi, Julia Kempe
2025	J	`jnl`	ImpMIA: Leveraging Implicit Bias for Membership Inference Attack under Realistic Scenarios. CoRR Yuval Golbari, Navve Wasserman, Gal Vardi, Michal Irani
2025	J	`jnl`	On the Hardness of Learning Regular Expressions. CoRR Idan Attias, Lev Reyzin, Nathan Srebro, Gal Vardi
2025	J	`jnl`	Provable Unlearning with Gradient Ascent on Two-Layer ReLU Neural Networks. CoRR Odelia Melamed, Gilad Yehudai, Gal Vardi
2025	J	`jnl`	Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes. CoRR Itamar Harel, Yonathan Wolanowsky, Gal Vardi, Nathan Srebro, Daniel Soudry
2025	A*	`conf`	Trained Transformer Classifiers Generalize and Exhibit Benign Overfitting In-Context. ICLR Spencer Frei, Gal Vardi
2025	J	`jnl`	Transformers are almost optimal metalearners for linear classification. CoRR Roey Magen, Gal Vardi
2024	A*	`conf`	An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression. ICLR Lijia Zhou, James B. Simon, Gal Vardi, Nathan Srebro
2024	J	`jnl`	Approaching Deep Learning through the Spectral Dynamics of Weights. CoRR David Yunis, Kumar Kshitij Patel, Samuel Wheeler, Pedro Savarese, Gal Vardi, Karen Livescu, Michael Maire, Matthew R. Walter
2024	A*	`conf`	Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data. ICLR Zhiwei Xu, Yutong Wang, Spencer Frei, Gal Vardi, Wei Hu
2024	J	`jnl`	Benign Overfitting in Single-Head Attention. CoRR Roey Magen, Shuning Shang, Zhiwei Xu, Spencer Frei, Wei Hu, Gal Vardi
2024	J	`jnl`	Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks. CoRR Nikolaos Tsilivis, Gal Vardi, Julia Kempe
2024	A*	`conf`	Noisy Interpolation Learning with Shallow Univariate ReLU Networks. ICLR Nirmit Joshi, Gal Vardi, Nathan Srebro
2024	A*	`conf`	Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality. NeurIPS Marko Medvedev, Gal Vardi, Nati Srebro
2024	J	`jnl`	Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality. CoRR Marko Medvedev, Gal Vardi, Nathan Srebro
2024	J	`jnl`	Perspective Games. ACM Trans. Comput. Log. Orna Kupferman, Gal Vardi
2024	J	`jnl`	Provable Privacy Attacks on Trained Shallow Neural Networks. CoRR Guy Smorodinsky, Gal Vardi, Itay Safran
2024	A*	`conf`	Provable Tempered Overfitting of Minimal Nets and Typical Nets. NeurIPS Itamar Harel, William Hoza, Gal Vardi, Itay Evron, Nati Srebro, Daniel Soudry
2024	J	`jnl`	Provable Tempered Overfitting of Minimal Nets and Typical Nets. CoRR Itamar Harel, William M. Hoza, Gal Vardi, Itay Evron, Nathan Srebro, Daniel Soudry
2024	J	`jnl`	Reconstructing Training Data From Real World Models Trained with Transfer Learning. CoRR Yakir Oz, Gilad Yehudai, Gal Vardi, Itai Antebi, Michal Irani, Niv Haim
2024	J	`jnl`	Trained Transformer Classifiers Generalize and Exhibit Benign Overfitting In-Context. CoRR Spencer Frei, Gal Vardi
2023	J	`jnl`	Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Data Manifolds. CoRR Odelia Melamed, Gilad Yehudai, Gal Vardi
2023	A*	`conf`	Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces. NeurIPS Odelia Melamed, Gilad Yehudai, Gal Vardi
2023	J	`jnl`	An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression. CoRR Lijia Zhou, James B. Simon, Gal Vardi, Nathan Srebro
2023	J	`jnl`	Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data. CoRR Zhiwei Xu, Yutong Wang, Spencer Frei, Gal Vardi, Wei Hu
2023	A*	`conf`	Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization. COLT Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro
2023	J	`jnl`	Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization. CoRR Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro
2023	A*	`conf`	Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy. NeurIPS Amit Daniely, Nati Srebro, Gal Vardi
2023	A*	`conf`	Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses. NeurIPS Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi, Yakir Oz, Yaniv Nikankin, Michal Irani
2023	J	`jnl`	Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses. CoRR Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi, Yakir Oz, Yaniv Nikankin, Michal Irani
2023	J	`jnl`	Efficiently Learning Neural Networks: What Assumptions May Suffice? CoRR Amit Daniely, Nathan Srebro, Gal Vardi
2023	A*	`conf`	Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data. ICLR Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro, Wei Hu
2023	B	`conf`	Implicit Regularization Towards Rank Minimization in ReLU Networks. ALT Nadav Timor, Gal Vardi, Ohad Shamir
2023	A*	`conf`	Most Neural Networks Are Almost Learnable. NeurIPS Amit Daniely, Nati Srebro, Gal Vardi
2023	J	`jnl`	Most Neural Networks Are Almost Learnable. CoRR Amit Daniely, Nathan Srebro, Gal Vardi
2023	J	`jnl`	Noisy Interpolation Learning with Shallow Univariate ReLU Networks. CoRR Nirmit Joshi, Gal Vardi, Nathan Srebro
2023	J	`jnl`	On the Implicit Bias in Deep-Learning Algorithms. Commun. ACM Gal Vardi
2023	J	`jnl`	Reconstructing Training Data from Multiclass Neural Networks. CoRR Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi, Michal Irani
2023	A*	`conf`	The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks. NeurIPS Spencer Frei, Gal Vardi, Peter L. Bartlett, Nati Srebro
2023	J	`jnl`	The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks. CoRR Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro
2022	A*	`conf`	Gradient Methods Provably Converge to Non-Robust Networks. NeurIPS Gal Vardi, Gilad Yehudai, Ohad Shamir
2022	J	`jnl`	Gradient Methods Provably Converge to Non-Robust Networks. CoRR Gal Vardi, Gilad Yehudai, Ohad Shamir
2022	J	`jnl`	Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data. CoRR Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro, Wei Hu
2022	J	`jnl`	Implicit Regularization Towards Rank Minimization in ReLU Networks. CoRR Nadav Timor, Gal Vardi, Ohad Shamir
2022	A*	`conf`	On Margin Maximization in Linear and ReLU Networks. NeurIPS Gal Vardi, Ohad Shamir, Nati Srebro
2022	A*	`conf`	On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias. NeurIPS Itay Safran, Gal Vardi, Jason D. Lee
2022	J	`jnl`	On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias. CoRR Itay Safran, Gal Vardi, Jason D. Lee
2022	J	`jnl`	On the Implicit Bias in Deep-Learning Algorithms. CoRR Gal Vardi
2022	A*	`conf`	On the Optimal Memorization Power of ReLU Neural Networks. ICLR Gal Vardi, Gilad Yehudai, Ohad Shamir
2022	A*	`conf`	Reconstructing Training Data From Trained Neural Networks. NeurIPS Niv Haim, Gal Vardi, Gilad Yehudai, Ohad Shamir, Michal Irani
2022	J	`jnl`	Reconstructing Training Data from Trained Neural Networks. CoRR Niv Haim, Gal Vardi, Gilad Yehudai, Ohad Shamir, Michal Irani
2022	A*	`conf`	The Sample Complexity of One-Hidden-Layer Neural Networks. NeurIPS Gal Vardi, Ohad Shamir, Nati Srebro
2022	J	`jnl`	The Sample Complexity of One-Hidden-Layer Neural Networks. CoRR Gal Vardi, Ohad Shamir, Nathan Srebro
2022	A*	`conf`	Width is Less Important than Depth in ReLU Neural Networks. COLT Gal Vardi, Gilad Yehudai, Ohad Shamir
2022	J	`jnl`	Width is Less Important than Depth in ReLU Neural Networks. CoRR Gal Vardi, Gilad Yehudai, Ohad Shamir
2021	A*	`conf`	From Local Pseudorandom Generators to Hardness of Learning. COLT Amit Daniely, Gal Vardi
2021	J	`jnl`	From Local Pseudorandom Generators to Hardness of Learning. CoRR Amit Daniely, Gal Vardi
2021	A*	`conf`	Implicit Regularization in ReLU Networks with the Square Loss. COLT Gal Vardi, Ohad Shamir
2021	A*	`conf`	Learning a Single Neuron with Bias Using Gradient Descent. NeurIPS Gal Vardi, Gilad Yehudai, Ohad Shamir
2021	J	`jnl`	Learning a Single Neuron with Bias Using Gradient Descent. CoRR Gal Vardi, Gilad Yehudai, Ohad Shamir
2021	J	`jnl`	On Margin Maximization in Linear and ReLU Networks. CoRR Gal Vardi, Ohad Shamir, Nathan Srebro
2021	J	`jnl`	On the Optimal Memorization Power of ReLU Neural Networks. CoRR Gal Vardi, Gilad Yehudai, Ohad Shamir
2021	A*	`conf`	Size and Depth Separation in Approximating Benign Functions with Neural Networks. COLT Gal Vardi, Daniel Reichman, Toniann Pitassi, Ohad Shamir
2021	J	`jnl`	Size and Depth Separation in Approximating Natural Functions with Neural Networks. CoRR Gal Vardi, Daniel Reichman, Toniann Pitassi, Ohad Shamir
2020	A*	`conf`	Hardness of Learning Neural Networks with Natural Weights. NeurIPS Amit Daniely, Gal Vardi
2020	J	`jnl`	Hardness of Learning Neural Networks with Natural Weights. CoRR Amit Daniely, Gal Vardi
2020	J	`jnl`	Implicit Regularization in ReLU Networks with the Square Loss. CoRR Gal Vardi, Ohad Shamir
2020	A*	`conf`	Neural Networks with Small Weights and Depth-Separation Barriers. NeurIPS Gal Vardi, Ohad Shamir
2020	J	`jnl`	Neural Networks with Small Weights and Depth-Separation Barriers. CoRR Gal Vardi, Ohad Shamir
2020	J	`jnl`	Neural Networks with Small Weights and Depth-Separation Barriers. Electron. Colloquium Comput. Complex. Gal Vardi, Ohad Shamir
2019	J	`jnl`	Flow Logic. Log. Methods Comput. Sci. Orna Kupferman, Gal Vardi
2019	—	`—`	Graph-Theoretic Problems from the Viewpoint of Formal Methods (כותר נוסף בעברית: בעיות בתורת הגרפים מנקודת המבט של אימות פורמלי). Gal Vardi
2019	J	`jnl`	Multi-player flow games. Auton. Agents Multi Agent Syst. Shibashis Guha, Orna Kupferman, Gal Vardi
2019	A*	`conf`	Perspective Games. LICS Orna Kupferman, Gal Vardi
2018	J	`jnl`	Flow Logic. CoRR Orna Kupferman, Gal Vardi
2018	A	`conf`	Multi-Player Flow Games. AAMAS Shibashis Guha, Orna Kupferman, Gal Vardi
2018	J	`jnl`	On relative and probabilistic finite counterability. Formal Methods Syst. Des. Orna Kupferman, Gal Vardi
2018	B	`conf`	Spanning-Tree Games. MFCS Dan Hefetz, Orna Kupferman, Amir Lellouche, Gal Vardi
2018	A*	`conf`	The Unfortunate-Flow Problem. ICALP Orna Kupferman, Gal Vardi
2017	—	`conf`	Flow Games. FSTTCS Orna Kupferman, Gal Vardi, Moshe Y. Vardi
2017	B	`conf`	Flow Logic. CONCUR Orna Kupferman, Gal Vardi
2016	B	`conf`	Eulerian Paths with Regular Constraints. MFCS Orna Kupferman, Gal Vardi
2015	B	`conf`	On Relative and Probabilistic Finite Counterability. CSL Orna Kupferman, Gal Vardi