Learning Theory: 17th Annual Conference on Learning Theory, COLT 2004 Banff, Canada, July 1-4, 2004 Proceedings,9783540222828

Learning Theory: 17th Annual Conference on Learning Theory, COLT 2004 Banff, Canada, July 1-4, 2004 Proceedings

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ISBN13: 9783540222828
ISBN10: 3540222820
Format: Paperback
Pub. Date: 2004-08-31
Publisher(s): Springer Verlag
List Price: $171.79

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Summary

This book constitutes the refereed proceedings of the 17th Annual Conference on Learning Theory, COLT 2004, held in Banff, Canada in July 2004. The 46 revised full papers presented were carefully reviewed and selected from a total of 113 submissions. The papers are organized in topical sections on economics and game theory, online learning, inductive inference, probabilistic models, Boolean function learning, empirical processes, MDL, generalisation, clustering and distributed learning, boosting, kernels and probabilities, kernels and kernel matrices, and open problems.

Table of Contents

Economics and Game Theory
Towards a Characterization of Polynomial Preference Elicitation with Value Queries in Combinatorial Auctions
1(16)
Paolo Santi
Vincent Conitzer
Thomas Sandholm
Graphical Economics
17(16)
Sham M. Kakade
Michael Kearns
Luis E. Ortiz
Deterministic Calibration and Nash Equilibrium
33(16)
Sham M. Kakade
Dean P. Foster
Reinforcement Learning for Average Reward Zero-Sum Games
49(15)
Shie Mannor
OnLine Learning
Polynomial Time Prediction Strategy with Almost Optimal Mistake Probability
64(13)
Nader H. Bshouty
Minimizing Regret with Label Efficient Prediction
77(16)
Nicolo Cesa-Bianchi
Gabor Lugosi
Gilles Stoltz
Regret Bounds for Hierarchical Classification with Linear-Threshold Functions
93(16)
Nicolo Cesa-Bianchi
Alex Conconi
Claudio Gentile
Online Geometric Optimization in the Bandit Setting Against an Adaptive Adversary
109(15)
H. Brendan McMahan
Avrim Blum
Inductive Inference
Learning Classes of Probabilistic Automata
124(16)
Francois Denis
Yann Esposito
On the Learnability of E-pattern Languages over Small Alphabets
140(15)
Daniel Reidenbach
Replacing Limit Learners with Equally Powerful One-Shot Query Learners
155(15)
Steffen Lange
Sandra Zilles
Probabilistic Models
Concentration Bounds for Unigrams Language Model
170(16)
Evgeny Drukh
Yishay Mansour
Inferring Mixtures of Markov Chains
186(14)
Tugkan Batu
Sudipto Guha
Sampath Kannan
Boolean Function Learning
PExact = Exact Learning
200(10)
Dmitry Gavinsky
Avi Owshanko
Learning a Hidden Graph Using O(logn) Queries Per Edge
210(14)
Dana Angluin
Jiang Chen
Toward Attribute Efficient Learning of Decision Lists and Parities
224(15)
Adam R. Klivans
Rocco A. Servedio
Empirical Processes
Learning Over Compact Metric Spaces
239(16)
H. Quang Minh
Thomas Hofmann
A Function Representation for Learning in Banach Spaces
255(15)
Charles A. Micchelli
Massimiliano Pontil
Local Complexities for Empirical Risk Minimization
270(15)
Peter L. Bartlett
Shahar Mendelson
Petra Philips
Model Selection by Bootstrap Penalization for Classification
285(15)
Magalie Fromont
MDL
Convergence of Discrete MDL for Sequential Prediction
300(15)
Jan Poland
Marcus Hutter
On the Convergence of MDL Density Estimation
315(16)
Tong Zhang
Suboptimal Behavior of Bayes and MDL in Classification Under Misspecification
331(17)
Peter Grunwald
John Langford
Generalisation I
Learning Intersections of Halfspaces with a Margin
348(15)
Adam R. Klivans
Rocco A. Servedio
A General Convergence Theorem for the Decomposition Method
363(15)
Niko List
Hans Ulrich Simon
Generalisation II
Oracle Bounds and Exact Algorithm for Dyadic Classification Trees
378(15)
Gilles Blanchard
Christin Schafer
Yves Rozenholc
An Improved VC Dimension Bound for Sparse Polynomials
393(15)
Michael Schmitt
A New PAC Bound for Intersection-Closed Concept Classes
408(7)
Peter Auer
Ronald Ortner
Clustering and Distributed Learning
A Framework for Statistical Clustering with a Constant Time Approximation Algorithms for K-Median Clustering
415(12)
Shai Ben-David
Data Dependent Risk Bounds for Hierarchical Mixture of Experts Classifiers
427(15)
Arik Azran
Ron Meir
Consistency in Models for Communication Constrained Distributed Learning
442(15)
J.B. Predd
S.R. Kulkarni
H. V. Poor
On the Convergence of Spectral Clustering on Random Samples: The Normalized Case
457(15)
Ulrike von Luxburg
Olivier Bousquet
Mikhail Belkin
Boosting
Performance Guarantees for Regularized Maximum Entropy Density Estimation
472(15)
Miroslav Dudik
Steven J. Phillips
Robert E. Schapire
Learning Monotonic Linear Functions
487(15)
Adam Kalai
Boosting Based on a Smooth Margin
502(16)
Cynthia Rudin
Robert E. Schapire
Ingrid Daubechies
Kernels and Probabilities
Bayesian Networks and Inner Product Spaces
518(16)
Atsuyoshi Nakamura
Michael Schmitt
Niels Schmitt
Hans Ulrich Simon
An Inequality for Nearly Log-Concave Distributions with Applications to Learning
534(15)
Constantine Caramanis
Shie Mannor
Bayes and Tukey Meet at the Center Point
549(15)
Ran Gilad-Bachrach
Amir Navot
Naftali Tishby
Sparseness Versus Estimating Conditional Probabilities: Some Asymptotic Results
564(15)
Peter L. Bartlett
Ambuj Tewari
Kernels and Kernel Matrices
A Statistical Mechanics Analysis of Gram Matrix Eigenvalue Spectra
579(15)
David C. Hoyle
Magnus Rattray
Statistical Properties of Kernel Principal Component Analysis
594(15)
Laurent Zwald
Olivier Bousquet
Gilles Blanchard
Kernelizing Sorting, Permutation, and Alignment for Minimum Volume PCA
609(15)
Tony Jebara
Regularization and Semi-supervised Learning on Large Graphs
624(15)
Mikhail Belkin
Irina Matveeva
Partha Niyogi
Open Problems
Perceptron-Like Performance for Intersections of Halfspaces
639(2)
Adam R. Klivans
Rocco A. Servedio
The Optimal PAC Algorithm
641(2)
Manfred K. Warmuth
The Budgeted Multi-armed Bandit Problem
643(4)
Omid Madani
Daniel J. Lizotte
Russell Greiner
Author Index 647

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