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The 22nd International Conference
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The following papers have been accepted for ALT 2011.
There is no particular order in the list.
Please keep in mind that we need your final version until
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Please prepare your final version in accordance with the
Instructions for authors.
| Axioms for Rational Reinforcement Learning | Peter Sunehag and Marcus Hutter
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| Robust Learning of Automatic Classes of Languages |
Sanjay Jain, Eric Martin, and Frank Stephan
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| Learning and Classifying |
Sanjay Jain, Eric Martin, and Frank Stephan
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| Making Online Decisions with Bounded Memory |
Chi-Jen Lu and Wei-Fu Lu
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| Lipschitz Bandits without the Lipschitz Constant |
Sebastien Bubeck, Gilles Stoltz, and Jia Yuan Yu
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| Learning Relational Patterns |
Michael Geilke and Sandra Zilles
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| Distributional Learning of Simple Context-Free Tree Grammars |
Ryo Yoshinaka and Anna Kasprzik
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| Accelerated Training of Max-Margin Markov Networks with Kernels |
Xinhua Zhang, Ankan Saha, and S.V.N. Vishwanathan
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| On Upper-Confidence Bound Policies for Switching Bandit Problems |
Aurélien Garivier and Eric Moulines
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| Universal Knowledge-Seeking Agents |
Laurent Orseau
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| Asymptotically Optimal Agents |
Tor Lattimore and Marcus Hutter
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| Iterative Learning from Positive Data and Counters |
Timo Kötzing
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| Time Consistent Discounting |
Tor Lattimore and Marcus Hutter
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| Adaptive and Optimal Online Linear Regression on L1-balls |
Sebastien Gerchinovitz and Jia Yuan Yu
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| Deviations of Stochastic Bandit Regret |
Antoine Salomon and Jean-Yves Audibert
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| The Perceptron with Dynamic Margin |
Constantinos Panagiotakopoulos and Petroula Tsampouka
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| Domain Adaptation in Regression |
Corinna Cortes and Mehryar Mohri
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| Universal Prediction of Selected Bits |
Tor Lattimore, Marcus Hutter, and Vaibhav Gavane
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| Regret Minimization Algorithms for Pricing Lookback Options |
Eyal Gofer and Yishay Mansour
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| Upper-Confidence-Bound Algorithms for Active Learning in Multi-Armed Bandits |
Alexandra Carpentier, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos, and Peter Auer
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| On Noise-Tolerant Learning of Sparse Parities and Related Problems |
Elena Grigorescu, Lev Reyzin, and Santosh Vempala
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| Supervised Learning and Co-training |
Hans Simon, Balázs Szörényi, and Malte Darnstädt
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| Re-Adapting the Regularization of Weights for Non-Stationary Regression |
Nina Vaits and Koby Crammer
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| Semantic Communication for Simple Goals is Equivalent to On-Line Learning |
Brendan Juba and Santosh Vempala
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| Learning a Classifier When the Labeling is Known |
Shalev Ben-David and Shai Ben-David
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| Approximate Reduction from AUC Maximization to 1-norm Soft Margin Optimization |
Daiki Suehiro, Kohei Hatano and Eiji Takimoto
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| Competing Against the Best Nearest Neighbor Filter in Regression |
Arnak S. Dalalyan and Joseph Salmon
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| Combining Initial Segments of Lists | Manfred Warmuth, Wouter M. Koolen, and David P. Helmbold |