Dana Ron (auth.), Nader H. Bshouty, Claudio Gentile (eds.)3540729275, 3540729259, 9783540729273, 9783540729259
The 41 revised full papers presented together with 5 articles on open problems and 2 invited lectures were carefully reviewed and selected from a total of 92 submissions. The papers cover a wide range of topics and are organized in topical sections on unsupervised, semisupervised and active learning, statistical learning theory, inductive inference, regularized learning, kernel methods, SVM, online and reinforcement learning, learning algorithms and limitations on learning, dimensionality reduction, other approaches, and open problems.
Table of contents :
Front Matter….Pages –
Property Testing: A Learning Theory Perspective….Pages 1-2
Spectral Algorithms for Learning and Clustering….Pages 3-4
Minimax Bounds for Active Learning….Pages 5-19
Stability of k -Means Clustering….Pages 20-34
Margin Based Active Learning….Pages 35-50
Learning Large-Alphabet and Analog Circuits with Value Injection Queries….Pages 51-65
Teaching Dimension and the Complexity of Active Learning….Pages 66-81
Multi-view Regression Via Canonical Correlation Analysis….Pages 82-96
Aggregation by Exponential Weighting and Sharp Oracle Inequalities….Pages 97-111
Occam’s Hammer….Pages 112-126
Resampling-Based Confidence Regions and Multiple Tests for a Correlated Random Vector….Pages 127-141
Suboptimality of Penalized Empirical Risk Minimization in Classification….Pages 142-156
Transductive Rademacher Complexity and Its Applications….Pages 157-171
U-Shaped, Iterative, and Iterative-with-Counter Learning….Pages 172-186
Mind Change Optimal Learning of Bayes Net Structure….Pages 187-202
Learning Correction Grammars ….Pages 203-217
Mitotic Classes….Pages 218-232
Regret to the Best vs. Regret to the Average….Pages 233-247
Strategies for Prediction Under Imperfect Monitoring….Pages 248-262
Bounded Parameter Markov Decision Processes with Average Reward Criterion….Pages 263-277
On-Line Estimation with the Multivariate Gaussian Distribution….Pages 278-292
Generalised Entropy and Asymptotic Complexities of Languages….Pages 293-307
Q -Learning with Linear Function Approximation….Pages 308-322
How Good Is a Kernel When Used as a Similarity Measure?….Pages 323-335
Gaps in Support Vector Optimization….Pages 336-348
Learning Languages with Rational Kernels….Pages 349-364
Generalized SMO-Style Decomposition Algorithms….Pages 365-377
Learning Nested Halfspaces and Uphill Decision Trees….Pages 378-392
An Efficient Re-scaled Perceptron Algorithm for Conic Systems….Pages 393-408
A Lower Bound for Agnostically Learning Disjunctions….Pages 409-423
Sketching Information Divergences….Pages 424-438
Competing with Stationary Prediction Strategies….Pages 439-453
Improved Rates for the Stochastic Continuum-Armed Bandit Problem….Pages 454-468
Learning Permutations with Exponential Weights….Pages 469-483
Multitask Learning with Expert Advice….Pages 484-498
Online Learning with Prior Knowledge….Pages 499-513
Nonlinear Estimators and Tail Bounds for Dimension Reduction in l 1 Using Cauchy Random Projections….Pages 514-529
Sparse Density Estimation with ℓ 1 Penalties….Pages 530-543
ℓ 1 Regularization in Infinite Dimensional Feature Spaces….Pages 544-558
Prediction by Categorical Features: Generalization Properties and Application to Feature Ranking….Pages 559-573
Observational Learning in Random Networks….Pages 574-588
The Loss Rank Principle for Model Selection….Pages 589-603
Robust Reductions from Ranking to Classification….Pages 604-619
Rademacher Margin Complexity….Pages 620-621
Open Problems in Efficient Semi-supervised PAC Learning….Pages 622-624
Resource-Bounded Information Gathering for Correlation Clustering….Pages 625-627
Are There Local Maxima in the Infinite-Sample Likelihood of Gaussian Mixture Estimation?….Pages 628-629
When Is There a Free Matrix Lunch?….Pages 630-632
Back Matter….Pages –
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