Steve Hanneke

Computer Science · Physical Sciences

19h-index2.3kcitations130works0.12yr avg
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Research Topics

Machine Learning and Algorithms(90), Algorithms and Data Compression(27), Domain Adaptation and Few-Shot Learning(26), Machine Learning and Data Classification(25), Advanced Bandit Algorithms Research(20)

Publications130 total

When More Data Doesn't Help: Limits of Adaptation in Multitask Learning
arXiv (Cornell University)·2026Open Access
A Theory of Universal Agnostic Learning
arXiv (Cornell University)·2026Open Access
When More Data Doesn't Help: Limits of Adaptation in Multitask Learning
ArXiv.org·2026Open Access
A Theory of Universal Agnostic Learning
ArXiv.org·2026Open Access
Optimal Mistake Bounds for Transductive Online Learning
arXiv (Cornell University)·2025Open Access
Sample Complexity of Agnostic Multiclass Classification: Natarajan Dimension Strikes Back
arXiv (Cornell University)·2025Open Access
Uniform Convergence Beyond Glivenko-Cantelli
arXiv (Cornell University)·2025Open Access
Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension
SIAM Journal on Computing·2025
Private List Learnability vs. Online List Learnability
arXiv (Cornell University)·2025Open Access
Tradeoffs between Mistakes and ERM Oracle Calls in Online and Transductive Online Learning
arXiv (Cornell University)·2025Open Access
Proofs as Explanations: Short Certificates for Reliable Predictions
arXiv (Cornell University)·2025Open Access
A Theory of Optimistically Universal Online Learnability for General Concept Classes
arXiv (Cornell University)·2025Open Access
Learning from Snapshots of Discrete and Continuous Data Streams
arXiv (Cornell University)·2024Open Access
On the ERM Principle in Meta-Learning
arXiv (Cornell University)·2024Open Access
Multiclass Transductive Online Learning
arXiv (Cornell University)·2024Open Access
Ramsey Theorems for Trees and a General ‘Private Learning Implies Online Learning’ Theorem
2024Open Access
Revisiting Agnostic PAC Learning
2024· 1 cited
Sample Compression Scheme Reductions
arXiv (Cornell University)·2024Open Access
A Complete Characterization of Learnability for Stochastic Noisy Bandits
arXiv (Cornell University)·2024Open Access
Adaptive Sample Aggregation In Transfer Learning
arXiv (Cornell University)·2024Open Access
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Frequent Co-authors

Lin F. Yang(10), Aryeh Kontorovich(6), Eric P. Xing(5), Jaime Carbonell(4), Maria-Florina Balcan(3), Omar Montasser(3), Nathan Srebro(3), Samory Kpotufe(3), Sivan Sabato(3), Roi Weiss(3), Shay Moran(3), Wenjie Fu(2), Yair Wiener(2), Ran El‐Yaniv(2), Nikita Zhivotovskiy(2), Varun Kanade(2), Jennifer Wortman Vaughan(1), Fan Guo(1), Wenjie Fu(1), Lev Reyzin(1)