Table of Contents

ALT '11 Logo

Editors' Introduction 1 - 13
Jyrki Kivinen, Csaba Szepesvári, Esko Ukkonen, and Thomas Zeugmann


INVITED PAPERS

Models for Autonomously Motivated Exploration in Reinforcement Learning,
Abstract.
14 - 17
Peter Auer, Shiau Hong Lim, and Chris Watkins.

On the Expressive Power of Deep Architectures,
Abstract.
18 - 36
Yoshua Bengio and Olivier Delalleau.

Optimal Estimation ,
Abstract.
37 - 37
Jorma Rissanen.

Learning from Label Preferences,
Abstract.
38 - 38
Eyke Hüllermeier and Johannes Fürnkranz.

Information Distance and Its Extensions,
Abstract.
39 - 39
Ming Li.


REGULAR CONTRIBUTIONS

Inductive Inference

Iterative Learning from Positive Data and Counters,
Abstract.
40 - 54
Timo Kötzing.

Robust Learning of Automatic Classes of Languages,
Abstract.
55 - 69
Sanjay Jain, Eric Martin, and Frank Stephan.

Learning and Classifying,
Abstract.
70 - 83
Sanjay Jain, Eric Martin, and Frank Stephan.
Learning Relational Patterns,
Abstract.
84 - 98
Michael Geilke and Sandra Zilles.


Regression

Adaptive and Optimal Online Linear Regression on ℓ1-Balls,
Abstract.
99 - 113
Sébastien Gerchinovitz and Jia Yuan Yu

Re-adapting the Regularization of Weights for Non-stationary Regression,
Abstract.
114 - 128
Nina Vaits, and Koby Crammer.

Competing against the Best Nearest Neighbor Filter in Regression,
Abstract.
129 - 143
Arnak S. Dalalyan, and Joseph Salmon.


Bandit Problems

Lipschitz Bandits without the Lipschitz Constant,
Abstract.
144 - 158
Sébastien Bubeck, Gilles Stoltz, and Jia Yuan Yu.

Deviations of Stochastic Bandit Regret,
Abstract.
159 - 173
Antoine Salomon and Jean-Yves Audibert.

On Upper-Confidence Bound Policies for Switching Bandit Problems,
Abstract.
174 - 188
Aurélien Garivier, and Eric Moulines.

Upper-Confidence-Bound Algorithms for Active Learning in Multi-armed Bandits,
Abstract.
189 - 203
Alexandra Carpentier, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos, and Peter Auer.

Online Learning

The Perceptron with Dynamic Margin,
Abstract.
204 - 218
Constantinos Panagiotakopoulos and Petroula Tsampouka.

Combining Initial Segments of Lists,
Abstract.
219 - 233
Manfred K. Warmuth, Wouter M. Koolen, and David P. Helmbold.

Regret Minimization Algorithms for Pricing Lookback Options,
Abstract.
234 - 248
Eyal Gofer and Yishay Mansour.

Making Online Decisions with Bounded Memory,
Abstract.
249 - 261
Chi-Jen Lu and Wei-Fu Lu.

Universal Prediction of Selected Bits,
Abstract.
262 - 276
Tor Lattimore, Marcus Hutter, and Vaibhav Gavane.

Semantic Communication for Simple Goals Is Equivalent to On-line Learning,
Abstract.
277 - 291
Brendan Juba, and Santosh Vempala.


Kernel and Margin Based Methods

Accelerated Training of Max-Margin Markov Networks with Kernels,
Abstract.
292 - 307
Xinhua Zhang, Ankan Saha, and S. V. N. Vishwanathan.

Domain Adaptation in Regression,
Abstract.
308 - 323
Corinna Cortes and Mehryar Mohri.

Approximate Reduction from AUC Maximization to 1-Norm Soft Margin Optimization,
Abstract.
324 - 337
Daiki Suehiro, Kohei Hatano, and Eiji Takimoto.


Intelligent Agents

Axioms for Rational Reinforcement Learning,
Abstract.
338 - 352
Peter Sunehag and Marcus Hutter.

Universal Knowledge-Seeking Agents,
Abstract.
353 - 367
Laurent Orseau.

Asymptotically Optimal Agents,
Abstract.
368 - 382
Tor Lattimore, and Marcus Hutter.

Time Consistent Discounting,
Abstract.
383 - 397
Tor Lattimore, and Marcus Hutter.


Other Learning Models

Distributional Learning of Simple Context-Free Tree Grammars,
Abstract.
398 - 412
Anna Kasprzik and Ryo Yoshinaka.

On Noise-Tolerant Learning of Sparse Parities and Related Problems,
Abstract.
413 - 424
Elena Grigorescu, Lev Reyzin, and Santosh Vempala.

Supervised Learning and Co-training,
Abstract.
425 - 439
Malte Darnstädt, Hans Ulrich Simon, and Balázs Szörényi.

Learning a Classifier when the Labeling Is Known,
Abstract.
440 - 451
Shalev Ben David and Shai Ben-David.


Erratum

Erratum: Learning without Coding,
Abstract.
452 - 452
Samuel E. Moelius III and Sandra Zilles.

Author Index 453


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