200 results on '"Shay Moran"'
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2. Learnability Gaps of Strategic Classification.
3. Dual VC Dimension Obstructs Sample Compression by Embeddings.
4. A Unified Characterization of Private Learnability via Graph Theory.
5. The Real Price of Bandit Information in Multiclass Classification.
6. Open problem: Direct Sums in Learning Theory.
7. List Sample Compression and Uniform Convergence.
8. Local Borsuk-Ulam, Stability, and Replicability.
9. Can Copyright Be Reduced to Privacy?
10. EnronSR: A Benchmark for Evaluating AI-Generated Email Replies.
11. Ramsey Theorems for Trees and a General 'Private Learning Implies Online Learning' Theorem.
12. Learnability Gaps of Strategic Classification.
13. Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs.
14. Dual VC Dimension Obstructs Sample Compression by Embeddings.
15. Fast Rates for Bandit PAC Multiclass Classification.
16. Credit Attribution and Stable Compression.
17. A Theory of Interpretable Approximations.
18. The Real Price of Bandit Information in Multiclass Classification.
19. Data Reconstruction: When You See It and When You Don't.
20. Learning-Augmented Algorithms with Explicit Predictors.
21. List Sample Compression and Uniform Convergence.
22. List Online Classification.
23. Fine-Grained Distribution-Dependent Learning Curves.
24. Multiclass Online Learning and Uniform Convergence.
25. Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension.
26. Universal Rates for Multiclass Learning.
27. Improper Multiclass Boosting.
28. Stability and Replicability in Learning.
29. Statistical Indistinguishability of Learning Algorithms.
30. Adversarial Resilience in Sequential Prediction via Abstention.
31. Black-Box Differential Privacy for Interactive ML.
32. The Bayesian Stability Zoo.
33. Multiclass Boosting: Simple and Intuitive Weak Learning Criteria.
34. A Trichotomy for Transductive Online Learning.
35. Monotone Learning.
36. A Characterization of Multiclass Learnability.
37. Uniform Brackets, Containers, and Combinatorial Macbeath Regions.
38. Active learning with label comparisons.
39. Understanding Generalization via Leave-One-Out Conditional Mutual Information.
40. A Resilient Distributed Boosting Algorithm.
41. Multiclass Boosting: Simple and Intuitive Weak Learning Criteria.
42. Adversarial Resilience in Sequential Prediction via Abstention.
43. Replicability and stability in learning.
44. A Trichotomy for Transductive Online Learning.
45. The Bayesian Stability Zoo.
46. Statistical Indistinguishability of Learning Algorithms.
47. Local Borsuk-Ulam, Stability, and Replicability.
48. Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension.
49. A Unified Characterization of Private Learnability via Graph Theory.
50. Diagonalization Games.
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