← Authors

Shay Moran

60 papers · 2016–2025 · 5 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (11) πŸ—ΊοΈ Taxonomy Completionist (51) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (9) 🌈 Renaissance Researcher (5) 🏠 Conference Loyalist (26) 🀝 Dynamic Duo (20) 🌱 Topic Pioneer πŸ”¬ Deep Specialist (36) πŸ† Keyword Champion (8) πŸ’Ž Century Club (60) πŸ“ˆ Trend Setter ⚑ Prolific Year (7) πŸ”₯ Unstoppable (10) πŸ—ƒοΈ Keyword Collector (169)

Conferences

COLT (28) NIPS (26) ICML (4) ALT (1) UAI (1)

Top co-authors

Steve Hanneke (20) Yishay Mansour (12) Amir Yehudayoff (9) Nataly Brukhim (6) Roi Livni (5) Noga Alon (5) Olivier Bousquet (4) Amin Karbasi (4) Jonathan Shafer (4) Raef Bassily (4)

Research topics

Privacy (3) Differential Privacy (2)

Keywords

pac learning (13) differential privacy (12) sample complexity (12) vc dimension (11) multiclass classification (9) uniform convergence (8) agnostic learning (7) learning theory (7) online learning (6) littlestone dimension (6) generalization bound (5) mistake bound (5) concept class (4) sample compression (3) public datum (3) bandit feedback (3) learning curve (3) learning rate (3) distributed learning (3) expert advice (3)

Papers

Of Dice and Games: A Theory of Generalized Boosting COLT 2025
A Fine-grained Characterization of PAC Learnability COLT 2025
The Role of Randomness in Stability ICML 2025
Open Problem: Data Selection for Regression Tasks COLT 2025
Private List Learnability vs. Online List Learnability COLT 2025
Data Selection for ERMs COLT 2025
Spherical Dimension COLT 2025
List Sample Compression and Uniform Convergence COLT 2024
Credit Attribution and Stable Compression NIPS 2024
Learnability Gaps of Strategic Classification COLT 2024
Dual VC Dimension Obstructs Sample Compression by Embeddings COLT 2024
A Theory of Interpretable Approximations COLT 2024
A Unified Characterization of Private Learnability via Graph Theory COLT 2024
The Real Price of Bandit Information in Multiclass Classification COLT 2024
Improved Sample Complexity for Multiclass PAC Learning NIPS 2024
Universal Rates for Active Learning NIPS 2024
Fast Rates for Bandit PAC Multiclass Classification NIPS 2024
Learning-Augmented Algorithms with Explicit Predictors NIPS 2024
Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs NIPS 2024
Open problem: Direct Sums in Learning Theory COLT 2024
List Online Classification COLT 2023
Multiclass Boosting: Simple and Intuitive Weak Learning Criteria NIPS 2023
Adversarial Resilience in Sequential Prediction via Abstention NIPS 2023
A Trichotomy for Transductive Online Learning NIPS 2023
The Bayesian Stability Zoo NIPS 2023
Black-Box Differential Privacy for Interactive ML NIPS 2023
Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension COLT 2023
Improper Multiclass Boosting COLT 2023
Universal Rates for Multiclass Learning COLT 2023
Multiclass Online Learning and Uniform Convergence COLT 2023
Fine-Grained Distribution-Dependent Learning Curves COLT 2023
Statistical Indistinguishability of Learning Algorithms ICML 2023
On Optimal Learning Under Targeted Data Poisoning NIPS 2022
Universal Rates for Interactive Learning NIPS 2022
Monotone Learning COLT 2022
A Resilient Distributed Boosting Algorithm ICML 2022
Active learning with label comparisons UAI 2022
Integral Probability Metrics PAC-Bayes Bounds NIPS 2022
Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games COLT 2021
Near Optimal Distributed Learning of Halfspaces with Two Parties COLT 2021
Multiclass Boosting and the Cost of Weak Learning NIPS 2021
Towards a Unified Information-Theoretic Framework for Generalization NIPS 2021
Closure Properties for Private Classification and Online Prediction COLT 2020
Private Query Release Assisted by Public Data ICML 2020
A Limitation of the PAC-Bayes Framework NIPS 2020
Synthetic Data Generators -- Sequential and Private NIPS 2020
Learning from Mixtures of Private and Public Populations NIPS 2020
Online Agnostic Boosting via Regret Minimization NIPS 2020
Proper Learning, Helly Number, and an Optimal SVM Bound COLT 2020
The Optimal Approximation Factor in Density Estimation COLT 2019
On Communication Complexity of Classification Problems COLT 2019
An adaptive nearest neighbor rule for classification NIPS 2019
Limits of Private Learning with Access to Public Data NIPS 2019
Private Learning Implies Online Learning: An Efficient Reduction NIPS 2019
Learning to Screen NIPS 2019
Private Center Points and Learning of Halfspaces COLT 2019
Learners that Use Little Information ALT 2018
Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues NIPS 2017
Supervised learning through the lens of compression NIPS 2016
Sign rank versus VC dimension COLT 2016