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2012 COLT COLT 2012

Consistency of Nearest Neighbor Classification under Selective Sampling

Abstract

This paper studies nearest neighbor classification in a model where unlabeled data points arrive in a stream, and the learner decides, for each one, whether to ask for its label. Are there generic ways to augment or modify any selective sampling strategy so as to ensure the consistency of the resulting nearest neighbor classifier?

🐣 Hot Topic Early Bird — active learning
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Sanjoy Dasgupta

Topics

Machine Learning > Core Methods > Classification Machine Learning > Learning Types > Active Learning Machine Learning > Optimization & Theory > Statistical Learning Machine Learning > Learning Types > Online Learning Machine Learning > Learning Types > Classification

Keywords

active learning online learning selective sampling nearest neighbor classification distribution-free learning stream learning
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