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Editors' Introduction | | 1 - 9
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Nader H. Bshouty,
Gilles Stoltz,
Nicolas Vayatis,
and
Thomas Zeugmann.
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INVITED PAPERS
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Declarative Modeling for Machine Learning and Data Mining,
Abstract.
| | 12 - 12
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Luc De Raedt
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Learnability beyond Uniform Convergence,
Abstract.
| | 13 - 16
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Shai Shalev-Shwartz
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Some Rates of Convergence for the Selected Lasso Estimator,
Abstract.
| | 17 - 33
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Pascal Massart and
Caroline Meynet.
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Recent Developments in Pattern Mining,
Abstract.
| | 34 - 34
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Toon Calders,
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Exploring Sequential Data,
Abstract.
| | 35 - 35
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Gilbert Ritschard
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REGULAR
CONTRIBUTIONS
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Inductive Inference
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Enlarging Learnable Classes,
Abstract.
| | 36 - 50
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Sanjay Jain,
Timo Kötzing,
and
Frank Stephan.
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Confident and Consistent Partial Learning of Recursive Functions,
Abstract.
| | 51 - 65
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Ziyuan Gao
and
Frank Stephan.
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Automatic Learning from Positive Data and Negative Counterexamples,
Abstract.
| | 66 - 80
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Sanjay Jain
and
Efim Kinber.
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Regular Inference as Vertex Coloring,
Abstract.
| | 81 - 95
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Christophe Costa Florêncio
and
Sicco Verwer.
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Teaching and PAC Learning
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Sauer's Bound for a Notion of Teaching Complexity,
Abstract.
| | 96 - 110
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Rahim Samei,
Pavel Semukhin,
Boting Yang,
and
Sandra Zilles.
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On the Learnability of Shuffle Ideals,
Abstract.
| | 111 - 123
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Dana Angluin,
James Aspnes,
and
Aryeh Kontorovich.
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Statistical Learning Theory and Classification
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New Analysis and Algorithm for Learning with Drifting Distributions,
Abstract.
| | 124 - 138
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Mehryar Mohri
and
Andres Muñoz Medina.
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On the Hardness of Domain Adaptation and the Utility of Unlabeled Target Samples,
Abstract.
| | 139 - 153
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Shai Ben-David
and
Ruth Urner.
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Efficient Protocols for Distributed Classification and Optimization,
Abstract.
| | 154 - 168
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Hal Daumé III,
Jeff M. Phillips,
Avishek Saha,
and
Suresh Venkatasubramanian.
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Relations between Models and Data
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The Safe Bayesian: Learning the Learning Rate via the Mixability Gap,
Abstract.
| | 169 - 183
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Peter Grünwald.
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Data Stability in Clustering: A Closer Look,
Abstract.
| | 184 - 198
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Lev Reyzin.
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Bandit Problems
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Thompson Sampling: An Asymptotically Optimal Finite-Time Analysis,
Abstract.
| | 199 - 213
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Emilie Kaufmann,
Nathaniel Korda,
and
Rémi Munos.
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Regret Bounds for Restless Markov Bandits,
Abstract.
| | 214 - 228
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Ronald Ortner,
Daniil Ryabko,
Peter Auer,
and
Rémi Munos.
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Minimax Number of Strata for Online Stratified Sampling Given Noisy Samples,
Abstract.
| | 229 - 244
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Alexandra Carpentier
and
Rémi Munos.
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Online Prediction of Individual Sequences
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Weighted Last-Step Min-Max Algorithm with Improved Sub-logarithmic Regret,
Abstract.
| | 245 - 259
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Edward Moroshko,
and
Koby Crammer.
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Online Prediction under Submodular Constraints,
Abstract.
| | 260 - 274
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Daiki Suehiro,
Kohei Hatano ,
Shuji Kijima,
Eiji Takimoto,
and
Kiyohito Nagano.
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Lower Bounds on Individual Sequence Regret,
Abstract.
| | 275 - 289
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Eyal Gofer
and
Yishay Mansour.
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A Closer Look at Adaptive Regret,
Abstract.
| | 290 - 304
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Dmitry Adamskiy,
Wouter M. Koolen,
Alexey Chernov,
and
Vladimir Vovk.
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Partial Monitoring with Side Information,
Abstract.
| | 305 - 319
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Gábor Bartók
and
Csaba Szepesvári.
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Other Models of Online Learning
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PAC Bounds for Discounted MDPs,
Abstract.
| | 320 - 334
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Tor Lattimore and
Marcus Hutter.
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Buy Low, Sell High,
Abstract.
| | 335 - 349
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Wouter M. Koolen
and
Vladimir Vovk.
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Kernelization of Matrix Updates, When and How?,
Abstract.
| | 350 - 364
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Manfred Warmuth,
Wojciech Kotłowski, and
Shuisheng Zhou.
| |
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Predictive Complexity and Generalized Entropy Rate of Stationary Ergodic Processes,
Abstract.
| | 365 - 379
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Mrinalkanti Ghosh and
Satyadev Nandakumar.
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Author Index
| | 381
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