Articles by Steve Hanneke

Claim page

Steve Hanneke

Activity

Upvotes

Folders

Articles

Learning from Snapshots of Discrete and Continuous Data Streams

8 December 2024 by Pramith Devulapalli and Steve Hanneke

Machine Learning

Universal Rates of Empirical Risk Minimization

3 December 2024 by Steve Hanneke and Mingyue Xu

Machine Learning

On the ERM Principle in Meta-Learning

26 November 2024 by Yannay Alon and others

Machine Learning

Multiclass Transductive Online Learning

3 November 2024 by Steve Hanneke and others

Machine Learning

Sample Compression Scheme Reductions

18 October 2024 by Idan Attias and others

Machine Learning

A Complete Characterization of Learnability for Stochastic Noisy Bandits

12 October 2024 by Steve Hanneke and Kun Wang

Machine Learning, Artificial Intelligence

Optimal Learners for Realizable Regression: PAC Learning and Online Learning

2 October 2024 by Idan Attias and others

Machine Learning, Artificial Intelligence

A More Unified Theory of Transfer Learning

29 August 2024 by Steve Hanneke and Samory Kpotufe

Machine Learning, Artificial Intelligence

Ramsey Theorems for Trees and a General 'Private Learning Implies Online Learning' Theorem

14 August 2024 by Simone Fioravanti and others at

Israel Institute of Technology

Machine Learning, Cryptography and Security

Revisiting Agnostic PAC Learning

29 July 2024 by Steve Hanneke and others

Machine Learning, Data Structures and Algorithms

Dual VC Dimension Obstructs Sample Compression by Embeddings

27 May 2024 by Zachary Chase and others

Discrete Mathematics, Machine Learning

A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability

5 May 2024 by Idan Attias and others

Machine Learning

Adversarially Robust PAC Learnability of Real-Valued Functions

5 May 2024 by Idan Attias and Steve Hanneke

Machine Learning

List Sample Compression and Uniform Convergence

16 March 2024 by Steve Hanneke and others

Machine Learning

The Dimension of Self-Directed Learning

20 February 2024 by Pramith Devulapalli and Steve Hanneke

Machine Learning

Efficient Agnostic Learning with Average Smoothness

13 February 2024 by Steve Hanneke and others

Machine Learning, Statistics Theory

Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs

12 February 2024 by Yuval Filmus and others

Machine Learning

Agnostic Sample Compression Schemes for Regression

3 February 2024 by Idan Attias and others

Machine Learning, Information Theory

Adversarial Resilience in Sequential Prediction via Abstention

25 January 2024 by Surbhi Goel and others

Machine Learning, Data Structures and Algorithms

A Trichotomy for Transductive Online Learning

29 November 2023 by Steve Hanneke and others

Machine Learning

Near-optimal learning with average Hölder smoothness

30 October 2023 by Steve Hanneke and others

Machine Learning, Statistics Theory

Reliable learning in challenging environments

29 October 2023 by Maria-Florina Balcan and others

Machine Learning, Cryptography and Security

Limits of Model Selection under Transfer Learning

12 October 2023 by Steve Hanneke and others

Machine Learning

Multiclass Online Learning and Uniform Convergence

7 July 2023 by Steve Hanneke and others

Machine Learning

Universal Rates for Multiclass Learning

5 July 2023 by Steve Hanneke and others

Machine Learning

Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension

3 July 2023 by Yuval Filmus and others

Machine Learning

Adversarial Rewards in Universal Learning for Contextual Bandits

12 June 2023 by Moise Blanchard and others

Machine Learning, Statistics Theory

Contextual Bandits and Optimistically Universal Learning

31 December 2022 by Moise Blanchard and others

Machine Learning, Statistics Theory

Fine-Grained Distribution-Dependent Learning Curves

10 November 2022 by Olivier Bousquet and others

Machine Learning, Computational Complexity

On Optimal Learning Under Targeted Data Poisoning

12 October 2022 by Steve Hanneke and others

Machine Learning, Cryptography and Security

This is an AI-generated summary

Key points

Topics

Machine Learning Statistics Theory Data Structures and Algorithms Artificial Intelligence Cryptography and Security Computational Complexity Probability Discrete Mathematics Information Theory Computational Geometry Computer Science and Game Theory Computation Methodology