Steve Hanneke
77 papers · 2005–2026 · 6 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 22 separate collaboration groups - the largest holds only 48% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Steve Hanneke?
7 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Liu Yang, Jaime Carbonell, Gongju Wang
9 papers
· 2010–2025
· AISTATS, COLT, ALT
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Reliable Active Apprenticeship Learning
ALT 2025
Bandit Learnability can be Undecidable
COLT 2023
Toward a General Theory of Online Selective Sampling: Trading Off Mistakes and Queries
AISTATS 2021
Statistical Learning under Nonstationary Mixing Processes
AISTATS 2019
Minimax Analysis of Active Learning
JMLR 2015
Activized Learning with Uniform Classification Noise
ICML 2013
Identifiability of Priors from Bounded Sample Sizes with Applications to Transfer Learning
COLT 2011
The Sample Complexity of Self-Verifying Bayesian Active Learning
AISTATS 2011
Negative Results for Active Learning with Convex Losses
AISTATS 2010
15 papers whose co-authors appear nowhere else under this name
Conference on Learning Theory 2026: Preface
COLT 2026
A Complete Characterization of Learnability for Stochastic Noisy Bandits
ALT 2025
The Star Number and Eluder Dimension: Elementary Observations About the Dimensions of Disagreement
COLT 2024
Universal Online Learning with Unbounded Losses: Memory Is All You Need
ALT 2022
Universally Consistent Online Learning with Arbitrarily Dependent Responses
ALT 2022
Learning Whenever Learning is Possible: Universal Learning under General Stochastic Processes
JMLR 2021
Open Problem: Is There an Online Learning Algorithm That Learns Whenever Online Learning Is Possible?
COLT 2021
Actively Avoiding Nonsense in Generative Models
COLT 2018
Algorithmic Learning Theory (ALT) 2017: Preface
ALT 2017
Refined Error Bounds for Several Learning Algorithms
JMLR 2016
The Optimal Sample Complexity of PAC Learning
JMLR 2016
A Compression Technique for Analyzing Disagreement-Based Active Learning
JMLR 2015
Activized Learning: Transforming Passive to Active with Improved Label Complexity
JMLR 2012
Robust Interactive Learning
COLT 2012
Network Completion and Survey Sampling
AISTATS 2005