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Algorithmic Learning Theory

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Cover of 'Algorithmic Learning Theory'

Table of Contents

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    Book Overview
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    Chapter 1 Editors’ Introduction
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    Chapter 2 Cellular Tree Classifiers
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    Chapter 3 A Survey of Preference-Based Online Learning with Bandit Algorithms
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    Chapter 4 A Map of Update Constraints in Inductive Inference
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    Chapter 5 On the Role of Update Constraints and Text-Types in Iterative Learning
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    Chapter 6 Parallel Learning of Automatic Classes of Languages
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    Chapter 7 Algorithmic Identification of Probabilities Is Hard
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    Chapter 8 Learning Boolean Halfspaces with Small Weights from Membership Queries
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    Chapter 9 On Exact Learning Monotone DNF from Membership Queries
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    Chapter 10 Learning Regular Omega Languages
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    Chapter 11 Selecting Near-Optimal Approximate State Representations in Reinforcement Learning
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    Chapter 12 Policy Gradients for CVaR-Constrained MDPs
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    Chapter 13 Bayesian Reinforcement Learning with Exploration
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    Chapter 14 Extreme State Aggregation beyond MDPs
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    Chapter 15 On Learning the Optimal Waiting Time
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    Chapter 16 Bandit Online Optimization over the Permutahedron
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    Chapter 17 Offline to Online Conversion
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    Chapter 18 A Chain Rule for the Expected Suprema of Gaussian Processes
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    Chapter 19 Generalization Bounds for Time Series Prediction with Non-stationary Processes
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    Chapter 20 Generalizing Labeled and Unlabeled Sample Compression to Multi-label Concept Classes
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    Chapter 21 Robust and Private Bayesian Inference
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    Chapter 22 Clustering, Hamming Embedding, Generalized LSH and the Max Norm
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    Chapter 23 Indefinitely Oscillating Martingales
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    Chapter 24 A Safe Approximation for Kolmogorov Complexity
Attention for Chapter 21: Robust and Private Bayesian Inference
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Readers on

31 Mendeley
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Chapter title
Robust and Private Bayesian Inference
Chapter number 21
Book title
Algorithmic Learning Theory
Published in
Lecture notes in computer science, January 2014
DOI 10.1007/978-3-319-11662-4_21
Book ISBNs
978-3-31-911661-7, 978-3-31-911662-4

Dimitrakakis, Christos, Nelson, Blaine, Mitrokotsa, Aikaterini, Rubinstein, Benjamin I. P., Christos Dimitrakakis, Blaine Nelson, Aikaterini Mitrokotsa, Benjamin I. P. Rubinstein


Auer, Peter, Zilles, Sandra, Zeugmann, Thomas, Clark, Alexander

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 2 6%
Canada 1 3%
Luxembourg 1 3%
Unknown 27 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 45%
Researcher 4 13%
Professor > Associate Professor 2 6%
Professor 2 6%
Student > Master 2 6%
Other 4 13%
Unknown 3 10%
Readers by discipline Count As %
Computer Science 19 61%
Mathematics 3 10%
Engineering 3 10%
Physics and Astronomy 1 3%
Business, Management and Accounting 1 3%
Other 0 0%
Unknown 4 13%