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Empirical Inference

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Cover of 'Empirical Inference'

Table of Contents

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    Book Overview
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    Chapter 1 In Hindsight: Doklady Akademii Nauk SSSR, 181(4), 1968
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    Chapter 2 On the Uniform Convergence of the Frequencies of Occurrence of Events to Their Probabilities
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    Chapter 3 Early History of Support Vector Machines
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    Chapter 4 Some Remarks on the Statistical Analysis of SVMs and Related Methods
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    Chapter 5 Explaining AdaBoost
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    Chapter 6 On the Relations and Differences Between Popper Dimension, Exclusion Dimension and VC-Dimension
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    Chapter 7 On Learnability, Complexity and Stability
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    Chapter 8 Loss Functions
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    Chapter 9 Statistical Learning Theory in Practice
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    Chapter 10 PAC-Bayesian Theory
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    Chapter 11 Kernel Ridge Regression
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    Chapter 12 Multi-task Learning for Computational Biology: Overview and Outlook
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    Chapter 13 Semi-supervised Learning in Causal and Anticausal Settings
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    Chapter 14 Strong Universal Consistent Estimate of the Minimum Mean Squared Error
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    Chapter 15 The Median Hypothesis
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    Chapter 16 Efficient Transductive Online Learning via Randomized Rounding
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    Chapter 17 Pivotal Estimation in High-Dimensional Regression via Linear Programming
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    Chapter 18 On Sparsity Inducing Regularization Methods for Machine Learning
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    Chapter 19 Sharp Oracle Inequalities in Low Rank Estimation
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    Chapter 20 On the Consistency of the Bootstrap Approach for Support Vector Machines and Related Kernel-Based Methods
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    Chapter 21 Kernels, Pre-images and Optimization
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    Chapter 22 Efficient Learning of Sparse Ranking Functions
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    Chapter 23 Direct Approximation of Divergences Between Probability Distributions
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