![](https://dblp.uni-trier.de/img/logo.ua.320x120.png)
![](https://dblp.uni-trier.de/img/dropdown.dark.16x16.png)
![](https://dblp.uni-trier.de/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
![search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
default search action
Gal Vardi
Person information
Refine list
![note](https://dblp.uni-trier.de/img/note-mark.dark.12x12.png)
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [j5]Orna Kupferman, Gal Vardi:
Perspective Games. ACM Trans. Comput. Log. 25(1): 4:1-4:26 (2024) - [c32]Nirmit Joshi, Gal Vardi, Nathan Srebro:
Noisy Interpolation Learning with Shallow Univariate ReLU Networks. ICLR 2024 - [c31]Zhiwei Xu, Yutong Wang, Spencer Frei, Gal Vardi, Wei Hu:
Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data. ICLR 2024 - [c30]Lijia Zhou, James B. Simon, Gal Vardi, Nathan Srebro:
An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression. ICLR 2024 - [i29]Yakir Oz, Gilad Yehudai, Gal Vardi, Itai Antebi, Michal Irani, Niv Haim:
Reconstructing Training Data From Real World Models Trained with Transfer Learning. CoRR abs/2407.15845 (2024) - 2023
- [j4]Gal Vardi:
On the Implicit Bias in Deep-Learning Algorithms. Commun. ACM 66(6): 86-93 (2023) - [c29]Nadav Timor, Gal Vardi, Ohad Shamir:
Implicit Regularization Towards Rank Minimization in ReLU Networks. ALT 2023: 1429-1459 - [c28]Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro:
Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization. COLT 2023: 3173-3228 - [c27]Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro, Wei Hu:
Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data. ICLR 2023 - [c26]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 - [c25]Amit Daniely, Nati Srebro, Gal Vardi:
Most Neural Networks Are Almost Learnable. NeurIPS 2023 - [c24]Amit Daniely, Nati Srebro, Gal Vardi:
Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy. NeurIPS 2023 - [c23]Spencer Frei, Gal Vardi, Peter L. Bartlett, Nati Srebro:
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks. NeurIPS 2023 - [c22]Odelia Melamed, Gilad Yehudai, Gal Vardi:
Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces. NeurIPS 2023 - [i28]Amit Daniely, Nathan Srebro, Gal Vardi:
Efficiently Learning Neural Networks: What Assumptions May Suffice? CoRR abs/2302.07426 (2023) - [i27]Odelia Melamed, Gilad Yehudai, Gal Vardi:
Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Data Manifolds. CoRR abs/2303.00783 (2023) - [i26]Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro:
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks. CoRR abs/2303.01456 (2023) - [i25]Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro:
Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization. CoRR abs/2303.01462 (2023) - [i24]Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi, Michal Irani:
Reconstructing Training Data from Multiclass Neural Networks. CoRR abs/2305.03350 (2023) - [i23]Amit Daniely, Nathan Srebro, Gal Vardi:
Most Neural Networks Are Almost Learnable. CoRR abs/2305.16508 (2023) - [i22]Lijia Zhou, James B. Simon, Gal Vardi, Nathan Srebro:
An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression. CoRR abs/2306.13185 (2023) - [i21]Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi, Yakir Oz, Yaniv Nikankin, Michal Irani:
Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses. CoRR abs/2307.01827 (2023) - [i20]Nirmit Joshi, Gal Vardi, Nathan Srebro:
Noisy Interpolation Learning with Shallow Univariate ReLU Networks. CoRR abs/2307.15396 (2023) - [i19]Zhiwei Xu, Yutong Wang, Spencer Frei, Gal Vardi, Wei Hu:
Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data. CoRR abs/2310.02541 (2023) - 2022
- [c21]Gal Vardi, Gilad Yehudai, Ohad Shamir:
Width is Less Important than Depth in ReLU Neural Networks. COLT 2022: 1249-1281 - [c20]Gal Vardi, Gilad Yehudai, Ohad Shamir:
On the Optimal Memorization Power of ReLU Neural Networks. ICLR 2022 - [c19]Niv Haim, Gal Vardi, Gilad Yehudai, Ohad Shamir, Michal Irani:
Reconstructing Training Data From Trained Neural Networks. NeurIPS 2022 - [c18]Itay Safran, Gal Vardi, Jason D. Lee:
On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias. NeurIPS 2022 - [c17]Gal Vardi, Ohad Shamir, Nati Srebro:
The Sample Complexity of One-Hidden-Layer Neural Networks. NeurIPS 2022 - [c16]Gal Vardi, Ohad Shamir, Nati Srebro:
On Margin Maximization in Linear and ReLU Networks. NeurIPS 2022 - [c15]Gal Vardi, Gilad Yehudai, Ohad Shamir:
Gradient Methods Provably Converge to Non-Robust Networks. NeurIPS 2022 - [i18]Nadav Timor, Gal Vardi, Ohad Shamir:
Implicit Regularization Towards Rank Minimization in ReLU Networks. CoRR abs/2201.12760 (2022) - [i17]Gal Vardi, Gilad Yehudai, Ohad Shamir:
Width is Less Important than Depth in ReLU Neural Networks. CoRR abs/2202.03841 (2022) - [i16]Gal Vardi, Gilad Yehudai, Ohad Shamir:
Gradient Methods Provably Converge to Non-Robust Networks. CoRR abs/2202.04347 (2022) - [i15]Gal Vardi, Ohad Shamir, Nathan Srebro:
The Sample Complexity of One-Hidden-Layer Neural Networks. CoRR abs/2202.06233 (2022) - [i14]Itay Safran, Gal Vardi, Jason D. Lee:
On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias. CoRR abs/2205.09072 (2022) - [i13]Niv Haim, Gal Vardi, Gilad Yehudai, Ohad Shamir, Michal Irani:
Reconstructing Training Data from Trained Neural Networks. CoRR abs/2206.07758 (2022) - [i12]Gal Vardi:
On the Implicit Bias in Deep-Learning Algorithms. CoRR abs/2208.12591 (2022) - [i11]Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro, Wei Hu:
Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data. CoRR abs/2210.07082 (2022) - 2021
- [c14]Amit Daniely, Gal Vardi:
From Local Pseudorandom Generators to Hardness of Learning. COLT 2021: 1358-1394 - [c13]Gal Vardi, Daniel Reichman, Toniann Pitassi, Ohad Shamir:
Size and Depth Separation in Approximating Benign Functions with Neural Networks. COLT 2021: 4195-4223 - [c12]Gal Vardi, Ohad Shamir:
Implicit Regularization in ReLU Networks with the Square Loss. COLT 2021: 4224-4258 - [c11]Gal Vardi, Gilad Yehudai, Ohad Shamir:
Learning a Single Neuron with Bias Using Gradient Descent. NeurIPS 2021: 28690-28700 - [i10]Amit Daniely, Gal Vardi:
From Local Pseudorandom Generators to Hardness of Learning. CoRR abs/2101.08303 (2021) - [i9]Gal Vardi, Daniel Reichman, Toniann Pitassi, Ohad Shamir:
Size and Depth Separation in Approximating Natural Functions with Neural Networks. CoRR abs/2102.00314 (2021) - [i8]Gal Vardi, Gilad Yehudai, Ohad Shamir:
Learning a Single Neuron with Bias Using Gradient Descent. CoRR abs/2106.01101 (2021) - [i7]Gal Vardi, Ohad Shamir, Nathan Srebro:
On Margin Maximization in Linear and ReLU Networks. CoRR abs/2110.02732 (2021) - [i6]Gal Vardi, Gilad Yehudai, Ohad Shamir:
On the Optimal Memorization Power of ReLU Neural Networks. CoRR abs/2110.03187 (2021) - 2020
- [c10]Amit Daniely, Gal Vardi:
Hardness of Learning Neural Networks with Natural Weights. NeurIPS 2020 - [c9]Gal Vardi, Ohad Shamir:
Neural Networks with Small Weights and Depth-Separation Barriers. NeurIPS 2020 - [i5]Gal Vardi, Ohad Shamir:
Neural Networks with Small Weights and Depth-Separation Barriers. CoRR abs/2006.00625 (2020) - [i4]Amit Daniely, Gal Vardi:
Hardness of Learning Neural Networks with Natural Weights. CoRR abs/2006.03177 (2020) - [i3]Gal Vardi, Ohad Shamir:
Implicit Regularization in ReLU Networks with the Square Loss. CoRR abs/2012.05156 (2020) - [i2]Gal Vardi, Ohad Shamir:
Neural Networks with Small Weights and Depth-Separation Barriers. Electron. Colloquium Comput. Complex. TR20 (2020)
2010 – 2019
- 2019
- [b1]Gal Vardi:
Graph-Theoretic Problems from the Viewpoint of Formal Methods (כותר נוסף בעברית: בעיות בתורת הגרפים מנקודת המבט של אימות פורמלי). Hebrew University of Jerusalem, Israel, 2019 - [j3]Shibashis Guha, Orna Kupferman, Gal Vardi
:
Multi-player flow games. Auton. Agents Multi Agent Syst. 33(6): 798-820 (2019) - [j2]Orna Kupferman, Gal Vardi:
Flow Logic. Log. Methods Comput. Sci. 15(4) (2019) - [c8]Orna Kupferman, Gal Vardi:
Perspective Games. LICS 2019: 1-13 - 2018
- [j1]Orna Kupferman, Gal Vardi
:
On relative and probabilistic finite counterability. Formal Methods Syst. Des. 52(2): 117-146 (2018) - [c7]Shibashis Guha, Orna Kupferman, Gal Vardi:
Multi-Player Flow Games. AAMAS 2018: 104-112 - [c6]Orna Kupferman, Gal Vardi:
The Unfortunate-Flow Problem. ICALP 2018: 157:1-157:14 - [c5]Dan Hefetz
, Orna Kupferman, Amir Lellouche, Gal Vardi:
Spanning-Tree Games. MFCS 2018: 35:1-35:16 - [i1]Orna Kupferman, Gal Vardi:
Flow Logic. CoRR abs/1806.05956 (2018) - 2017
- [c4]Orna Kupferman, Gal Vardi:
Flow Logic. CONCUR 2017: 9:1-9:18 - [c3]Orna Kupferman, Gal Vardi, Moshe Y. Vardi:
Flow Games. FSTTCS 2017: 38:38-38:16 - 2016
- [c2]Orna Kupferman, Gal Vardi:
Eulerian Paths with Regular Constraints. MFCS 2016: 62:1-62:15 - 2015
- [c1]Orna Kupferman, Gal Vardi:
On Relative and Probabilistic Finite Counterability. CSL 2015: 175-192
Coauthor Index
![](https://dblp.uni-trier.de/img/cog.dark.24x24.png)
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-08-20 23:02 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint