Learning Theory

20th Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA; June 13-15, 2007. Proceedings

Editors:

ISBN: 978-3-540-72925-9 (Print) 978-3-540-72927-3 (Online)

Table of contents (48 chapters)

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  1. Front Matter

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  2. Invited Presentations

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      Book Chapter

      Pages 1-2

      Property Testing: A Learning Theory Perspective

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      Pages 3-4

      Spectral Algorithms for Learning and Clustering

  3. Unsupervised, Semisupervised and Active Learning I

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      Pages 5-19

      Minimax Bounds for Active Learning

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      Pages 20-34

      Stability of k-Means Clustering

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      Pages 35-50

      Margin Based Active Learning

  4. Unsupervised, Semisupervised and Active Learning II

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      Pages 51-65

      Learning Large-Alphabet and Analog Circuits with Value Injection Queries

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      Pages 66-81

      Teaching Dimension and the Complexity of Active Learning

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      Pages 82-96

      Multi-view Regression Via Canonical Correlation Analysis

  5. Statistical Learning Theory

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      Pages 97-111

      Aggregation by Exponential Weighting and Sharp Oracle Inequalities

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      Pages 112-126

      Occam’s Hammer

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      Pages 127-141

      Resampling-Based Confidence Regions and Multiple Tests for a Correlated Random Vector

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      Pages 142-156

      Suboptimality of Penalized Empirical Risk Minimization in Classification

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      Pages 157-171

      Transductive Rademacher Complexity and Its Applications

  6. Inductive Inference

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      Pages 172-186

      U-Shaped, Iterative, and Iterative-with-Counter Learning

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      Pages 187-202

      Mind Change Optimal Learning of Bayes Net Structure

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      Pages 203-217

      Learning Correction Grammars

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      Pages 218-232

      Mitotic Classes

  7. Online and Reinforcement Learning I

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      Pages 233-247

      Regret to the Best vs. Regret to the Average

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      Pages 248-262

      Strategies for Prediction Under Imperfect Monitoring

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      Book Chapter

      Pages 263-277

      Bounded Parameter Markov Decision Processes with Average Reward Criterion

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