Learning Theory 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings / edited by John Shawe-Taylor, Yoram Singer.

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Bibliographic Details
Corporate Author:	SpringerLink (Online service)
Other Authors:	Shawe-Taylor, John (Editor), Singer, Yoram (Editor)
Format:	eBook
Language:	English
Published:	Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2004.
Edition:	1st ed. 2004.
Series:	Lecture Notes in Artificial Intelligence ; 3120 Springer eBook Collection.
Subjects:	Artificial intelligence. Mathematical logic. Algorithms. Computers. Electronic resources (E-books)
Online Access:	Click to view e-book
Holy Cross Note:	Loaded electronically. Electronic access restricted to members of the Holy Cross Community.

Table of Contents:

Economics and Game Theory
Towards a Characterization of Polynomial Preference Elicitation with Value Queries in Combinatorial Auctions
Graphical Economics
Deterministic Calibration and Nash Equilibrium
Reinforcement Learning for Average Reward Zero-Sum Games
OnLine Learning
Polynomial Time Prediction Strategy with Almost Optimal Mistake Probability
Minimizing Regret with Label Efficient Prediction
Regret Bounds for Hierarchical Classification with Linear-Threshold Functions
Online Geometric Optimization in the Bandit Setting Against an Adaptive Adversary
Inductive Inference
Learning Classes of Probabilistic Automata
On the Learnability of E-pattern Languages over Small Alphabets
Replacing Limit Learners with Equally Powerful One-Shot Query Learners
Probabilistic Models
Concentration Bounds for Unigrams Language Model
Inferring Mixtures of Markov Chains
Boolean Function Learning
PExact = Exact Learning
Learning a Hidden Graph Using O(log n) Queries Per Edge
Toward Attribute Efficient Learning of Decision Lists and Parities
Empirical Processes
Learning Over Compact Metric Spaces
A Function Representation for Learning in Banach Spaces
Local Complexities for Empirical Risk Minimization
Model Selection by Bootstrap Penalization for Classification
MDL
Convergence of Discrete MDL for Sequential Prediction
On the Convergence of MDL Density Estimation
Suboptimal Behavior of Bayes and MDL in Classification Under Misspecification
Generalisation I
Learning Intersections of Halfspaces with a Margin
A General Convergence Theorem for the Decomposition Method
Generalisation II
Oracle Bounds and Exact Algorithm for Dyadic Classification Trees
An Improved VC Dimension Bound for Sparse Polynomials
A New PAC Bound for Intersection-Closed Concept Classes
Clustering and Distributed Learning
A Framework for Statistical Clustering with a Constant Time Approximation Algorithms for K-Median Clustering
Data Dependent Risk Bounds for Hierarchical Mixture of Experts Classifiers
Consistency in Models for Communication Constrained Distributed Learning
On the Convergence of Spectral Clustering on Random Samples: The Normalized Case
Boosting
Performance Guarantees for Regularized Maximum Entropy Density Estimation
Learning Monotonic Linear Functions
Boosting Based on a Smooth Margin
Kernels and Probabilities
Bayesian Networks and Inner Product Spaces
An Inequality for Nearly Log-Concave Distributions with Applications to Learning
Bayes and Tukey Meet at the Center Point
Sparseness Versus Estimating Conditional Probabilities: Some Asymptotic Results
Kernels and Kernel Matrices
A Statistical Mechanics Analysis of Gram Matrix Eigenvalue Spectra
Statistical Properties of Kernel Principal Component Analysis
Kernelizing Sorting, Permutation, and Alignment for Minimum Volume PCA
Regularization and Semi-supervised Learning on Large Graphs
Open Problems
Perceptron-Like Performance for Intersections of Halfspaces
The Optimal PAC Algorithm
The Budgeted Multi-armed Bandit Problem.

Learning Theory 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings / edited by John Shawe-Taylor, Yoram Singer.

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