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Editors' Introduction | | 1 - 7
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Peter Auer,
Alexander Clark,
Thomas Zeugmann,
and
Sandra Zilles
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FULL
INVITED PAPERS
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Cellular Tree Classifiers,
Abstract.
| | 8 - 17
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Gérard Biau and
Luc Devroye
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A Survey of Preference-Based Online Learning with Bandit Algorithms,
Abstract.
| | 18 - 39
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Róbert Busa-Fekete
and
Eike Hüllermeier
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REGULAR
CONTRIBUTIONS
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Inductive Inference
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A Map of Update Constraints in Inductive Inference,
Abstract.
| | 40 - 54
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Timo Kötzing and
Raphaela Palenta
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On the Role of Update Constraints and Text-Types in Iterative Learning,
Abstract.
| | 55 - 69
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Sanjay Jain,
Timo Kötzing,
Junqi Ma, and
Frank Stephan
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Parallel Learning of Automatic Classes of Languages,
Abstract.
| | 70 - 84
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Sanjay Jain
and
Efim Kinber
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Algorithmic Identification of Probabilities Is Hard,
Abstract.
| | 85 - 95
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Laurent Bienvenu,
Benoît Monin,
and
Alexander Shen
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Exact Learning from Queries
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Learning Boolean Halfspaces with Small Weights from Membership Queries,
Abstract.
| | 96 - 110
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Hasan Abasi, Ali Z. Abdi,
and
Nader H. Bshouty
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On Exact Learning Monotone DNF from Membership Queries,
Abstract.
| | 111 - 124
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Hasan Abasi,
Nader H. Bshouty
and
Hanna Mazzawi
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Learning Regular Omega Languages,
Abstract.
| | 125 - 139
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Dana Angluin
and
Dana Fisman
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Reinforcement Learning
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Selecting Near-Optimal Approximate State Representations in Reinforcement Learning,
Abstract.
| | 140 - 154
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Ronald Ortner,
Odalric-Ambrym Maillard,
and
Daniil Ryabko
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Policy Gradients for CVaR-Constrained MDPs,
Abstract.
| | 155 - 169
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L. A. Prashanth
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Bayesian Reinforcement Learning with Exploration,
Abstract.
| | 170 - 184
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Tor Lattimore
and
Marcus Hutter
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Extreme State Aggregation beyond MDPs,
Abstract.
| | 185 - 199
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Marcus Hutter
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Online Learning and Learning with Bandit Information
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On Learning the Optimal Waiting Time,
Abstract.
| | 200 - 214
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Tor Lattimore,
András György,
and
Csaba Szepesvári
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Bandit Online Optimization over the Permutahedron,
Abstract.
| | 215 - 229
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Nir Ailon,
Kohei Hatano,
and
Eiji Takimoto
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Offline to Online Conversion,
Abstract.
| | 230 - 244
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Marcus Hutter
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Statistical Learning Theory
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A Chain Rule for the Expected Suprema of Gaussian Processes,
Abstract.
| | 245 - 259
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Andreas Maurer
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Generalization Bounds for Time Series Prediction with Non-stationary Processes,
Abstract.
| | 260 - 274
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Vitaly Kuznetsov and
Mehryar Mohri
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Generalizing Labeled and Unlabeled Sample Compression to Multi-label Concept Classes,
Abstract.
| | 275 - 290
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Rahim Samei,
Boting Yang,
and
Sandra Zilles
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Privacy, Clustering, MDL, and Kolmogorov Complexity
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Robust and Private Bayesian Inference,
Abstract.
| | 291 - 305
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Christos Dimitrakakis,
Blaine Nelson,
Aikaterini Mitrokotsa,
and
Benjamin I. P. Rubinstein
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Clustering, Hamming Embedding, Generalized LSH and the Max Norm,
Abstract.
| | 306 - 320
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Behnam Neyshabur,
Yury Makarychev,
and
Nathan Srebro
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Indefinitely Oscillating Martingales,
Abstract.
| | 321 - 335
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Jan Leike and
Marcus Hutter
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A Safe Approximation for Kolmogorov Complexity,
Abstract.
| | 336 - 350
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Peter Bloem, Francisco Mota, Steven de Rooij,
Luís Antunes, Pieter Adriaans
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Author Index
| | 351
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