Front matter
149-169
Agnostic Learning Nonconvex Function Classes
Shahar Mendelson and Robert C. Williamson
14-28
Entropy, Combinatorial Dimensions and Random Averages
Shahar Mendelson and Roman Vershynin
1-4
Geometric Parameters of Kernel Machines
Shahar Mendelson
79-97
Localized Rademacher Complexities
Peter L. Bartlett, Olivier Bousquet and Shahar Mendelson
164-171
Some Local Measures of Complexity of Convex Hulls and Generalization Bounds
Olivier Bousquet, Vladimir Koltchinskii and Dmitriy Panchenko
99-147
Path Kernels and Multiplicative Updates
Eiji Takimoto and Manfred K. Warmuth
45-78
Predictive Complexity and Information
Michael V. Vyugin and Vladimir V. V’yugin
171-192
Mixability and the Existence of Weak Complexities
Yuri Kalnishkan and Michael V. Vyugin
129-140
A Second-Order Perceptron Algorithm
Nicolò Cesa-Bianchi, Alex Conconi and Claudio Gentile
9-43
Tracking Linear-Threshold Concepts with Winnow
Chris Mesterharm
153-168
Learning Tree Languages from Text
Henning Fernau
195-228
Polynomial Time Inductive Inference of Ordered Tree Patterns with Internal Structured Variables from Positive Data
Yusuke Suzuki, Ryuta Akanuma, Takayoshi Shoudai, Tetsuhiro Miyahara and Tomoyuki Uchida
185-200
Inferring Deterministic Linear Languages
Colin de la Higuera and Jose Oncina
132-163
Merging Uniform Inductive Learners
Sandra Zilles
123-127
The Speed Prior: A New Simplicity Measure Yielding Near-Optimal Computable Predictions
Jürgen Schmidhuber
1-7
New Lower Bounds for Statistical Query Learning
Ke Yang
211-234
Exploring Learnability between Exact and PAC
Nader H. Bshouty, Jeffrey C. Jackson and Christino Tamon
193-209
PAC Bounds for Multi-armed Bandit and Markov Decision Processes
Eyal Even-Dar, Shie Mannor and Yishay Mansour
141-142
Bounds for the Minimum Disagreement Problem with Applications to Learning Theory
Nader H. Bshouty and Lynn Burroughs
172-188
On the Proper Learning of Axis Parallel Concepts
Nader H. Bshouty and Lynn Burroughs
35-80
A Consistent Strategy for Boosting Algorithms
Gábor Lugosi and Nicolas Vayatis
1-34
The Consistency of Greedy Algorithms for Classification
Shie Mannor, Ron Meir and Tong Zhang
93-111
Maximizing the Margin with Boosting
Gunnar Rätsch and Manfred K. Warmuth
235-254
Performance Guarantees for Hierarchical Clustering
Sanjoy Dasgupta
229-255
Self-Optimizing and Pareto-Optimal Policies in General Environments Based on Bayes-Mixtures
Marcus Hutter
81-131
Prediction and Dimension
Lance Fortnow and Jack H. Lutz
5-11
Learning the Internet
Christos Papadimitriou
Back matter