Shay Moran

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 177

Top Venues

CoRR

COLT

NeurIPS

Electron. Colloquium Comput. Complex.

Publications

Zachary Chase, Bogdan Chornomaz, Steve Hanneke, Shay Moran, Amir Yehudayoff
Dual VC Dimension Obstructs Sample Compression by Embeddings. CoRR (2024)
Liad Erez, Alon Cohen, Tomer Koren, Yishay Mansour, Shay Moran
The Real Price of Bandit Information in Multiclass Classification. COLT (2024)
Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen
A Theory of Interpretable Approximations. COLT (2024)
Niva Elkin-Koren, Uri Hacohen, Roi Livni, Shay Moran
Can Copyright Be Reduced to Privacy? FORC (2024)
Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen
A Theory of Interpretable Approximations. CoRR (2024)
Lee Cohen, Yishay Mansour, Shay Moran, Han Shao
Learnability Gaps of Strategic Classification. COLT (2024)
Edith Cohen, Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer, Eliad Tsfadia
Data Reconstruction: When You See It and When You Don't. CoRR (2024)
Simone Fioravanti, Steve Hanneke, Shay Moran, Hilla Schefler, Iska Tsubari
Ramsey Theorems for Trees and a General 'Private Learning Implies Online Learning' Theorem. CoRR (2024)
Steve Hanneke, Shay Moran, Tom Waknine
Open problem: Direct Sums in Learning Theory. COLT (2024)
Lee Cohen, Yishay Mansour, Shay Moran, Han Shao
Learnability Gaps of Strategic Classification. CoRR (2024)
Noga Alon, Shay Moran, Hilla Schefler, Amir Yehudayoff
A Unified Characterization of Private Learnability via Graph Theory. COLT (2024)
Liad Erez, Alon Cohen, Tomer Koren, Yishay Mansour, Shay Moran
Fast Rates for Bandit PAC Multiclass Classification. CoRR (2024)
Steve Hanneke, Shay Moran, Tom Waknine
List Sample Compression and Uniform Convergence. COLT (2024)
Liad Erez, Alon Cohen, Tomer Koren, Yishay Mansour, Shay Moran
The Real Price of Bandit Information in Multiclass Classification. CoRR (2024)
Steve Hanneke, Shay Moran, Tom Waknine
List Sample Compression and Uniform Convergence. CoRR (2024)
Shay Moran, Roei Davidson, Nir Grinberg
EnronSR: A Benchmark for Evaluating AI-Generated Email Replies. ICWSM (2024)
Marek Eliás, Haim Kaplan, Yishay Mansour, Shay Moran
Learning-Augmented Algorithms with Explicit Predictors. CoRR (2024)
Yuval Filmus, Steve Hanneke, Idan Mehalel, Shay Moran
Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs. CoRR (2024)
Zachary Chase, Bogdan Chornomaz, Shay Moran, Amir Yehudayoff
Local Borsuk-Ulam, Stability, and Replicability. STOC (2024)
Zachary Chase, Bogdan Chornomaz, Steve Hanneke, Shay Moran, Amir Yehudayoff
Dual VC Dimension Obstructs Sample Compression by Embeddings. COLT (2024)
Roi Livni, Shay Moran, Kobbi Nissim, Chirag Pabbaraju
Credit Attribution and Stable Compression. CoRR (2024)
Noga Alon, Olivier Bousquet, Kasper Green Larsen, Shay Moran, Shlomo Moran
Diagonalization Games. Electron. Colloquium Comput. Complex. (2023)
Niva Elkin-Koren, Uri Hacohen, Roi Livni, Shay Moran
Can Copyright be Reduced to Privacy? CoRR (2023)
Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer
On Differentially Private Online Predictions. CoRR (2023)
Olivier Bousquet, Steve Hanneke, Shay Moran, Jonathan Shafer, Ilya O. Tolstikhin
Fine-Grained Distribution-Dependent Learning Curves. COLT (2023)
Nataly Brukhim, Amit Daniely, Yishay Mansour, Shay Moran
Multiclass Boosting: Simple and Intuitive Weak Learning Criteria. NeurIPS (2023)
Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer
Black-Box Differential Privacy for Interactive ML. NeurIPS (2023)
Zachary Chase, Bogdan Chornomaz, Shay Moran, Amir Yehudayoff
Local Borsuk-Ulam, Stability, and Replicability. CoRR (2023)
Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas
Statistical Indistinguishability of Learning Algorithms. CoRR (2023)
Yuval Filmus, Steve Hanneke, Idan Mehalel, Shay Moran
Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension. COLT (2023)
Steve Hanneke, Shay Moran, Jonathan Shafer
A Trichotomy for Transductive Online Learning. NeurIPS (2023)
Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty
Adversarial Resilience in Sequential Prediction via Abstention. CoRR (2023)
Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty
Adversarial Resilience in Sequential Prediction via Abstention. NeurIPS (2023)
Zachary Chase, Shay Moran, Amir Yehudayoff
Stability and Replicability in Learning. FOCS (2023)
Nataly Brukhim, Steve Hanneke, Shay Moran
Improper Multiclass Boosting. COLT (2023)
Zachary Chase, Shay Moran, Amir Yehudayoff
Replicability and stability in learning. CoRR (2023)
Noga Alon, Shay Moran, Hilla Schefler, Amir Yehudayoff
A Unified Characterization of Private Learnability via Graph Theory. CoRR (2023)
Shay Moran, Ohad Sharon, Iska Tsubari
List Online Classification. CoRR (2023)
Yuval Filmus, Steve Hanneke, Idan Mehalel, Shay Moran
Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension. CoRR (2023)
Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas
Statistical Indistinguishability of Learning Algorithms. ICML (2023)
Steve Hanneke, Shay Moran, Qian Zhang
Universal Rates for Multiclass Learning. CoRR (2023)
Steve Hanneke, Shay Moran, Vinod Raman, Unique Subedi, Ambuj Tewari
Multiclass Online Learning and Uniform Convergence. COLT (2023)
Steve Hanneke, Shay Moran, Qian Zhang
Universal Rates for Multiclass Learning. COLT (2023)
Noga Alon, Alon Gonen, Elad Hazan, Shay Moran
Boosting Simple Learners. TheoretiCS 2 (2023)
Shay Moran, Hilla Schefler, Jonathan Shafer
The Bayesian Stability Zoo. CoRR (2023)
Steve Hanneke, Shay Moran, Jonathan Shafer
A Trichotomy for Transductive Online Learning. CoRR (2023)
Shay Moran, Hilla Schefler, Jonathan Shafer
The Bayesian Stability Zoo. NeurIPS (2023)
Noga Alon, Olivier Bousquet, Kasper Green Larsen, Shay Moran, Shlomo Moran
Diagonalization Games. CoRR (2023)
Shay Moran, Ohad Sharon, Iska Tsubari, Sivan Yosebashvili
List Online Classification. COLT (2023)
Nataly Brukhim, Amit Daniely, Yishay Mansour, Shay Moran
Multiclass Boosting: Simple and Intuitive Weak Learning Criteria. CoRR (2023)
Steve Hanneke, Amin Karbasi, Mohammad Mahmoody, Idan Mehalel, Shay Moran
On Optimal Learning Under Targeted Data Poisoning. NeurIPS (2022)
Mahdi Haghifam, Shay Moran, Daniel M. Roy, Gintare Karolina Dziugiate
Understanding Generalization via Leave-One-Out Conditional Mutual Information. ISIT (2022)
Olivier Bousquet, Haim Kaplan, Aryeh Kontorovich, Yishay Mansour, Shay Moran, Menachem Sadigurschi, Uri Stemmer
Differentially-Private Bayes Consistency. CoRR (2022)
Olivier Bousquet, Amit Daniely, Haim Kaplan, Yishay Mansour, Shay Moran, Uri Stemmer
Monotone Learning. COLT (2022)
Olivier Bousquet, Amit Daniely, Haim Kaplan, Yishay Mansour, Shay Moran, Uri Stemmer
Monotone Learning. CoRR (2022)
Olivier Bousquet, Mark Braverman, Gillat Kol, Klim Efremenko, Shay Moran
Statistically Near-Optimal Hypothesis Selection. FOCS (2022)
Gal Yona, Shay Moran, Gal Elidan, Amir Globerson
Active learning with label comparisons. UAI (2022)
Steve Hanneke, Amin Karbasi, Mohammad Mahmoody, Idan Mehalel, Shay Moran
On Optimal Learning Under Targeted Data Poisoning. CoRR (2022)
Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas
Universal Rates for Interactive Learning. NeurIPS (2022)
Noga Alon, Steve Hanneke, Ron Holzman, Shay Moran
A Theory of PAC Learnability of Partial Concept Classes. FOCS (2022)
Maryanthe Malliaris, Shay Moran
The unstable formula theorem revisited. CoRR (2022)
Olivier Bousquet, Steve Hanneke, Shay Moran, Jonathan Shafer, Ilya O. Tolstikhin
Fine-Grained Distribution-Dependent Learning Curves. CoRR (2022)
Noga Alon, Mark Bun, Roi Livni, Maryanthe Malliaris, Shay Moran
Private and Online Learnability Are Equivalent. J. ACM 69 (4) (2022)
Ron Amit, Baruch Epstein, Shay Moran, Ron Meir
Integral Probability Metrics PAC-Bayes Bounds. CoRR (2022)
Yuval Filmus, Idan Mehalel, Shay Moran
A Resilient Distributed Boosting Algorithm. ICML (2022)
Nataly Brukhim, Daniel Carmon, Irit Dinur, Shay Moran, Amir Yehudayoff
A Characterization of Multiclass Learnability. CoRR (2022)
Nataly Brukhim, Daniel Carmon, Irit Dinur, Shay Moran, Amir Yehudayoff
A Characterization of Multiclass Learnability. FOCS (2022)
Mahdi Haghifam, Shay Moran, Daniel M. Roy, Gintare Karolina Dziugaite
Understanding Generalization via Leave-One-Out Conditional Mutual Information. CoRR (2022)
Yuval Filmus, Idan Mehalel, Shay Moran
A Resilient Distributed Boosting Algorithm. CoRR (2022)
Gal Yona, Shay Moran, Gal Elidan, Amir Globerson
Active Learning with Label Comparisons. CoRR (2022)
Josef Minarík, Shay Moran, Michael Skotnica
How Expressive Are Friendly School Partitions? CoRR (2022)
Ron Amit, Baruch Epstein, Shay Moran, Ron Meir
Integral Probability Metrics PAC-Bayes Bounds. NeurIPS (2022)
Kunal Dutta, Arijit Ghosh, Shay Moran
Uniform Brackets, Containers, and Combinatorial Macbeath Regions. ITCS (2022)
Jérémie Chalopin, Victor Chepoi, Shay Moran, Manfred K. Warmuth
Unlabeled sample compression schemes and corner peelings for ample and maximum classes. J. Comput. Syst. Sci. 127 (2022)
Nataly Brukhim, Daniel Carmon, Irit Dinur, Shay Moran, Amir Yehudayoff
A Characterization of Multiclass Learnability. Electron. Colloquium Comput. Complex. (2022)
Mark Braverman, Gillat Kol, Shay Moran, Raghuvansh R. Saxena
Near Optimal Distributed Learning of Halfspaces with Two Parties. COLT (2021)
Noga Alon, Omri Ben-Eliezer, Yuval Dagan, Shay Moran, Moni Naor, Eylon Yogev
Adversarial Laws of Large Numbers and Optimal Regret in Online Classification. CoRR (2021)
Steve Hanneke, Roi Livni, Shay Moran
Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games. CoRR (2021)
Olivier Bousquet, Mark Braverman, Klim Efremenko, Gillat Kol, Shay Moran
Statistically Near-Optimal Hypothesis Selection. CoRR (2021)
Mahdi Haghifam, Gintare Karolina Dziugaite, Shay Moran, Daniel M. Roy
Towards a Unified Information-Theoretic Framework for Generalization. CoRR (2021)
Mahdi Haghifam, Gintare Karolina Dziugaite, Shay Moran, Dan Roy
Towards a Unified Information-Theoretic Framework for Generalization. NeurIPS (2021)
Shai Ben-David, Pavel Hrubes, Shay Moran, Amir Shpilka, Amir Yehudayoff
Learnability can be independent of set theory (invited paper). STOC (2021)
Nataly Brukhim, Elad Hazan, Shay Moran, Indraneel Mukherjee, Robert E. Schapire
Multiclass Boosting and the Cost of Weak Learning. NeurIPS (2021)
Noga Alon, Steve Hanneke, Ron Holzman, Shay Moran
A Theory of PAC Learnability of Partial Concept Classes. CoRR (2021)
Olivier Bousquet, Mark Braverman, Gillat Kol, Klim Efremenko, Shay Moran
Statistically Near-Optimal Hypothesis Selection. FOCS (2021)
Yuval Dagan, Yuval Filmus, Daniel Kane, Shay Moran
The Entropy of Lies: Playing Twenty Questions with a Liar. ITCS (2021)
Steve Hanneke, Roi Livni, Shay Moran
Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games. COLT (2021)
Tomer Moran, Shay Moran, Shlomo Moran
Elementary Derivations of the Euclidean Hurwitz Algebras Adapted from Gadi Moran's last paper. Am. Math. Mon. 128 (8) (2021)
Kunal Dutta, Arijit Ghosh, Shay Moran
Uniform Brackets, Containers, and Combinatorial Macbeath Regions. CoRR (2021)
Noga Alon, Omri Ben-Eliezer, Yuval Dagan, Shay Moran, Moni Naor, Eylon Yogev
Adversarial laws of large numbers and optimal regret in online classification. STOC (2021)
Olivier Bousquet, Steve Hanneke, Shay Moran, Ramon van Handel, Amir Yehudayoff
A theory of universal learning. STOC (2021)
Maryanthe Malliaris, Shay Moran
Agnostic Online Learning and Excellent Sets. CoRR (2021)
Noga Alon, Steve Hanneke, Ron Holzman, Shay Moran
A Theory of PAC Learnability of Partial Concept Classes. FOCS (2021)
Noga Alon, Alon Gonen, Elad Hazan, Shay Moran
Boosting simple learners. STOC (2021)
Raef Bassily, Albert Cheu, Shay Moran, Aleksandar Nikolov, Jonathan R. Ullman, Zhiwei Steven Wu
Private Query Release Assisted by Public Data. ICML (2020)
Shay Moran, Ido Nachum, Itai Panasoff, Amir Yehudayoff
On the Perceptron's Compression. CiE (2020)
Roi Livni, Shay Moran
A Limitation of the PAC-Bayes Framework. CoRR (2020)
Nataly Brukhim, Xinyi Chen, Elad Hazan, Shay Moran
Online Agnostic Boosting via Regret Minimization. NeurIPS (2020)
Noga Alon, Amos Beimel, Shay Moran, Uri Stemmer
Closure Properties for Private Classification and Online Prediction. CoRR (2020)
Stijn Cambie, Bogdan Chornomaz, Zeev Dvir, Yuval Filmus, Shay Moran
A Sauer-Shelah-Perles Lemma for Lattices. Electron. J. Comb. 27 (4) (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Shay Moran