Shay Moran

Orcid: 0000-0002-8662-2737

According to our database1, Shay Moran authored at least 121 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of three.
  • Erdős number3 of two.

Timeline

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Bibliography

2024
Credit Attribution and Stable Compression.
CoRR, 2024

Fast Rates for Bandit PAC Multiclass Classification.
CoRR, 2024

Data Reconstruction: When You See It and When You Don't.
CoRR, 2024

Learning-Augmented Algorithms with Explicit Predictors.
CoRR, 2024

Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs.
CoRR, 2024

Local Borsuk-Ulam, Stability, and Replicability.
Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 2024

EnronSR: A Benchmark for Evaluating AI-Generated Email Replies.
Proceedings of the Eighteenth International AAAI Conference on Web and Social Media, 2024

Can Copyright Be Reduced to Privacy?
Proceedings of the 5th Symposium on Foundations of Responsible Computing, 2024

Ramsey Theorems for Trees and a General 'Private Learning Implies Online Learning' Theorem.
Proceedings of the 65th IEEE Annual Symposium on Foundations of Computer Science, 2024

Open problem: Direct Sums in Learning Theory.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

List Sample Compression and Uniform Convergence.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

The Real Price of Bandit Information in Multiclass Classification.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

A Unified Characterization of Private Learnability via Graph Theory.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

A Theory of Interpretable Approximations.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Learnability Gaps of Strategic Classification.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Dual VC Dimension Obstructs Sample Compression by Embeddings.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023
Boosting Simple Learners.
TheoretiCS, 2023

Diagonalization Games.
Electron. Colloquium Comput. Complex., 2023

Replicability and stability in learning.
CoRR, 2023

List Online Classification.
CoRR, 2023

On Differentially Private Online Predictions.
CoRR, 2023

The Bayesian Stability Zoo.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Black-Box Differential Privacy for Interactive ML.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Trichotomy for Transductive Online Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adversarial Resilience in Sequential Prediction via Abstention.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multiclass Boosting: Simple and Intuitive Weak Learning Criteria.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Statistical Indistinguishability of Learning Algorithms.
Proceedings of the International Conference on Machine Learning, 2023

Stability and Replicability in Learning.
Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

List Online Classification.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Universal Rates for Multiclass Learning.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Multiclass Online Learning and Uniform Convergence.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Improper Multiclass Boosting.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Fine-Grained Distribution-Dependent Learning Curves.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022
Unlabeled sample compression schemes and corner peelings for ample and maximum classes.
J. Comput. Syst. Sci., 2022

Private and Online Learnability Are Equivalent.
J. ACM, 2022

A Characterization of Multiclass Learnability.
Electron. Colloquium Comput. Complex., 2022

The unstable formula theorem revisited.
CoRR, 2022

Differentially-Private Bayes Consistency.
CoRR, 2022

How Expressive Are Friendly School Partitions?
CoRR, 2022

Active learning with label comparisons.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Universal Rates for Interactive Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On Optimal Learning Under Targeted Data Poisoning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Integral Probability Metrics PAC-Bayes Bounds.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Understanding Generalization via Leave-One-Out Conditional Mutual Information.
Proceedings of the IEEE International Symposium on Information Theory, 2022

Uniform Brackets, Containers, and Combinatorial Macbeath Regions.
Proceedings of the 13th Innovations in Theoretical Computer Science Conference, 2022

A Resilient Distributed Boosting Algorithm.
Proceedings of the International Conference on Machine Learning, 2022

Monotone Learning.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
Elementary Derivations of the Euclidean Hurwitz Algebras Adapted from Gadi Moran's last paper.
Am. Math. Mon., 2021

Agnostic Online Learning and Excellent Sets.
CoRR, 2021

A theory of universal learning.
Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Learnability can be independent of set theory (invited paper).
Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Adversarial laws of large numbers and optimal regret in online classification.
Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Towards a Unified Information-Theoretic Framework for Generalization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Multiclass Boosting and the Cost of Weak Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The Entropy of Lies: Playing Twenty Questions with a Liar.
Proceedings of the 12th Innovations in Theoretical Computer Science Conference, 2021

Statistically Near-Optimal Hypothesis Selection.
Proceedings of the 62nd IEEE Annual Symposium on Foundations of Computer Science, 2021

A Theory of PAC Learnability of Partial Concept Classes.
Proceedings of the 62nd IEEE Annual Symposium on Foundations of Computer Science, 2021

Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games.
Proceedings of the Conference on Learning Theory, 2021

Near Optimal Distributed Learning of Halfspaces with Two Parties.
Proceedings of the Conference on Learning Theory, 2021

2020
On Weak ε-Nets and the Radon Number.
Discret. Comput. Geom., 2020

On the Information Complexity of Proper Learners for VC Classes in the Realizable Case.
CoRR, 2020

A Sauer-Shelah-Perles Lemma for Lattices.
Electron. J. Comb., 2020

A Limitation of the PAC-Bayes Framework.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Online Agnostic Boosting via Regret Minimization.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Synthetic Data Generators - Sequential and Private.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning from Mixtures of Private and Public Populations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Private Query Release Assisted by Public Data.
Proceedings of the 37th International Conference on Machine Learning, 2020

An Equivalence Between Private Classification and Online Prediction.
Proceedings of the 61st IEEE Annual Symposium on Foundations of Computer Science, 2020

Proper Learning, Helly Number, and an Optimal SVM Bound.
Proceedings of the Conference on Learning Theory, 2020

Closure Properties for Private Classification and Online Prediction.
Proceedings of the Conference on Learning Theory, 2020

On the Perceptron's Compression.
Proceedings of the Beyond the Horizon of Computability, 2020

2019
Author Correction: Learnability can be undecidable.
Nat. Mach. Intell., 2019

Learnability can be undecidable.
Nat. Mach. Intell., 2019

Convex Set Disjointness, Distributed Learning of Halfspaces, and LP Feasibility.
CoRR, 2019

Learning and Generalization for Matching Problems.
CoRR, 2019

Passing Tests without Memorizing: Two Models for Fooling Discriminators.
CoRR, 2019

Twenty (Short) Questions.
Comb., 2019

Approximate Nonnegative Rank is Equivalent to the Smooth Rectangle Bound.
Comput. Complex., 2019

Private PAC learning implies finite Littlestone dimension.
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019

Private Learning Implies Online Learning: An Efficient Reduction.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning to Screen.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Limits of Private Learning with Access to Public Data.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

An adaptive nearest neighbor rule for classification.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On Weak epsilon-Nets and the Radon Number.
Proceedings of the 35th International Symposium on Computational Geometry, 2019

The Optimal Approximation Factor in Density Estimation.
Proceedings of the Conference on Learning Theory, 2019

Private Center Points and Learning of Halfspaces.
Proceedings of the Conference on Learning Theory, 2019

2018
Generalized comparison trees for point-location problems.
Electron. Colloquium Comput. Complex., 2018

Are Two (Samples) Really Better Than One? On the Non-Asymptotic Performance of Empirical Revenue Maximization.
CoRR, 2018

A Sauer-Shelah-Perles Lemma for Sumsets.
Electron. J. Comb., 2018

Are Two (Samples) Really Better Than One?
Proceedings of the 2018 ACM Conference on Economics and Computation, 2018

Learners that Use Little Information.
Proceedings of the Algorithmic Learning Theory, 2018

2017
Active classification with comparison queries.
Electron. Colloquium Comput. Complex., 2017

On Communication Complexity of Classification Problems.
Electron. Colloquium Comput. Complex., 2017

Near-optimal linear decision trees for k-SUM and related problems.
Electron. Colloquium Comput. Complex., 2017

A learning problem that is independent of the set theory ZFC axioms.
CoRR, 2017

Learners that Leak Little Information.
CoRR, 2017

Twenty (simple) questions.
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Generalization and simplification in machine learning.
PhD thesis, 2016

Sample Compression Schemes for VC Classes.
J. ACM, 2016

Simple and optimal randomized fault-tolerant rumor spreading.
Distributed Comput., 2016

On statistical learning via the lens of compression.
CoRR, 2016

Supervised learning through the lens of compression.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Hitting Set for Hypergraphs of Low VC-dimension.
Proceedings of the 24th Annual European Symposium on Algorithms, 2016

Sign rank versus VC dimension.
Proceedings of the 29th Conference on Learning Theory, 2016

Labeled Compression Schemes for Extremal Classes.
Proceedings of the Algorithmic Learning Theory - 27th International Conference, 2016

2015
Proper PAC learning is compressing.
Electron. Colloquium Comput. Complex., 2015

Teaching and compressing for low VC-dimension.
Electron. Colloquium Comput. Complex., 2015

Shattered Sets and the Hilbert Function.
Electron. Colloquium Comput. Complex., 2015

Matchings vs hitting sets among half-spaces in low dimensional euclidean spaces.
CoRR, 2015

Compressing and Teaching for Low VC-Dimension.
Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015

Node-Balancing by Edge-Increments.
Proceedings of the Algorithms - ESA 2015, 2015

2014
Fooling Pairs in Randomized Communication Complexity.
Electron. Colloquium Comput. Complex., 2014

Internal compression of protocols to entropy.
Electron. Colloquium Comput. Complex., 2014

Sign rank, VC dimension and spectral gaps.
Electron. Colloquium Comput. Complex., 2014

2013
A note on average-case sorting.
Electron. Colloquium Comput. Complex., 2013

Direct Sum Fails for Zero Error Average Communication.
Electron. Colloquium Comput. Complex., 2013

Shattering, Graph Orientations, and Connectivity.
Electron. J. Comb., 2013

2012
Shattering-Extremal Systems
CoRR, 2012

Fast Fault Tolerant Rumor Spreading with Minimum Message Complexity
CoRR, 2012


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