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Publication search results
found 187 matches
- 2024
- Yuval Filmus, Steve Hanneke, Idan Mehalel, Shay Moran:
Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs. CoRR abs/2402.07453 (2024) - Lee Cohen, Yishay Mansour, Shay Moran, Han Shao:
Learnability Gaps of Strategic Classification. CoRR abs/2402.19303 (2024) - Marek Eliás, Haim Kaplan, Yishay Mansour, Shay Moran:
Learning-Augmented Algorithms with Explicit Predictors. CoRR abs/2403.07413 (2024) - Steve Hanneke, Shay Moran, Tom Waknine:
List Sample Compression and Uniform Convergence. CoRR abs/2403.10889 (2024) - 2023
- Noga Alon, Alon Gonen, Elad Hazan, Shay Moran:
Boosting Simple Learners. TheoretiCS 2 (2023) - Olivier Bousquet, Steve Hanneke, Shay Moran, Jonathan Shafer, Ilya O. Tolstikhin:
Fine-Grained Distribution-Dependent Learning Curves. COLT 2023: 5890-5924 - Nataly Brukhim, Steve Hanneke, Shay Moran:
Improper Multiclass Boosting. COLT 2023: 5433-5452 - Yuval Filmus, Steve Hanneke, Idan Mehalel, Shay Moran:
Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension. COLT 2023: 773-836 - Steve Hanneke, Shay Moran, Vinod Raman, Unique Subedi, Ambuj Tewari:
Multiclass Online Learning and Uniform Convergence. COLT 2023: 5682-5696 - Steve Hanneke, Shay Moran, Qian Zhang:
Universal Rates for Multiclass Learning. COLT 2023: 5615-5681 - Shay Moran, Ohad Sharon, Iska Tsubari, Sivan Yosebashvili:
List Online Classification. COLT 2023: 1885-1913 - Zachary Chase, Shay Moran, Amir Yehudayoff:
Stability and Replicability in Learning. FOCS 2023: 2430-2439 - Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas:
Statistical Indistinguishability of Learning Algorithms. ICML 2023: 15586-15622 - Nataly Brukhim, Amit Daniely, Yishay Mansour, Shay Moran:
Multiclass Boosting: Simple and Intuitive Weak Learning Criteria. NeurIPS 2023 - Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty:
Adversarial Resilience in Sequential Prediction via Abstention. NeurIPS 2023 - Steve Hanneke, Shay Moran, Jonathan Shafer:
A Trichotomy for Transductive Online Learning. NeurIPS 2023 - Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer:
Black-Box Differential Privacy for Interactive ML. NeurIPS 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 abs/2301.01924 (2023) - Yuval Filmus, Steve Hanneke, Idan Mehalel, Shay Moran:
Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension. CoRR abs/2302.13849 (2023) - Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer:
On Differentially Private Online Predictions. CoRR abs/2302.14099 (2023) - Shay Moran, Ohad Sharon, Iska Tsubari:
List Online Classification. CoRR abs/2303.15383 (2023) - Zachary Chase, Shay Moran, Amir Yehudayoff:
Replicability and stability in learning. CoRR abs/2304.03757 (2023) - Noga Alon, Shay Moran, Hilla Schefler, Amir Yehudayoff:
A Unified Characterization of Private Learnability via Graph Theory. CoRR abs/2304.03996 (2023) - Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas:
Statistical Indistinguishability of Learning Algorithms. CoRR abs/2305.14311 (2023) - Niva Elkin-Koren, Uri Hacohen, Roi Livni, Shay Moran:
Can Copyright be Reduced to Privacy? CoRR abs/2305.14822 (2023) - Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty:
Adversarial Resilience in Sequential Prediction via Abstention. CoRR abs/2306.13119 (2023) - Nataly Brukhim, Amit Daniely, Yishay Mansour, Shay Moran:
Multiclass Boosting: Simple and Intuitive Weak Learning Criteria. CoRR abs/2307.00642 (2023) - Steve Hanneke, Shay Moran, Qian Zhang:
Universal Rates for Multiclass Learning. CoRR abs/2307.02066 (2023) - Shay Moran, Hilla Schefler, Jonathan Shafer:
The Bayesian Stability Zoo. CoRR abs/2310.18428 (2023)
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