Abstract is missing.
- Editors' IntroductionNader H. Bshouty, Gilles Stoltz, Nicolas Vayatis, Thomas Zeugmann. 1-11 [doi]
- Declarative Modeling for Machine Learning and Data MiningLuc De Raedt. 12 [doi]
- Learnability beyond Uniform ConvergenceShai Shalev-Shwartz. 13-16 [doi]
- Some Rates of Convergence for the Selected Lasso EstimatorPascal Massart, Caroline Meynet. 17-33 [doi]
- Recent Developments in Pattern MiningToon Calders. 34 [doi]
- Exploring Sequential DataGilbert Ritschard. 35 [doi]
- Enlarging Learnable ClassesSanjay Jain, Timo Kötzing, Frank Stephan. 36-50 [doi]
- Confident and Consistent Partial Learning of Recursive FunctionsZiyuan Gao, Frank Stephan. 51-65 [doi]
- Automatic Learning from Positive Data and Negative CounterexamplesSanjay Jain, Efim B. Kinber. 66-80 [doi]
- Regular Inference as Vertex ColoringChristophe Costa Florêncio, Sicco Verwer. 81-95 [doi]
- Sauer's Bound for a Notion of Teaching ComplexityRahim Samei, Pavel Semukhin, Boting Yang, Sandra Zilles. 96-110 [doi]
- On the Learnability of Shuffle IdealsDana Angluin, James Aspnes, Aryeh Kontorovich. 111-123 [doi]
- New Analysis and Algorithm for Learning with Drifting DistributionsMehryar Mohri, Andres Muñoz Medina. 124-138 [doi]
- On the Hardness of Domain Adaptation and the Utility of Unlabeled Target SamplesShai Ben-David, Ruth Urner. 139-153 [doi]
- Efficient Protocols for Distributed Classification and OptimizationHal Daumé III, Jeff M. Phillips, Avishek Saha, Suresh Venkatasubramanian. 154-168 [doi]
- The Safe Bayesian - Learning the Learning Rate via the Mixability GapPeter Grünwald. 169-183 [doi]
- Data Stability in Clustering: A Closer LookLev Reyzin. 184-198 [doi]
- Thompson Sampling: An Asymptotically Optimal Finite-Time AnalysisEmilie Kaufmann, Nathaniel Korda, Rémi Munos. 199-213 [doi]
- Regret Bounds for Restless Markov BanditsRonald Ortner, Daniil Ryabko, Peter Auer, Rémi Munos. 214-228 [doi]
- Minimax Number of Strata for Online Stratified Sampling Given Noisy SamplesAlexandra Carpentier, Rémi Munos. 229-244 [doi]
- Weighted Last-Step Min-Max Algorithm with Improved Sub-logarithmic RegretEdward Moroshko, Koby Crammer. 245-259 [doi]
- Online Prediction under Submodular ConstraintsDaiki Suehiro, Kohei Hatano, Shuji Kijima, Eiji Takimoto, Kiyohito Nagano. 260-274 [doi]
- Lower Bounds on Individual Sequence RegretEyal Gofer, Yishay Mansour. 275-289 [doi]
- A Closer Look at Adaptive RegretDmitry Adamskiy, Wouter M. Koolen, Alexey V. Chernov, Vladimir Vovk. 290-304 [doi]
- Partial Monitoring with Side InformationGábor Bartók, Csaba Szepesvári. 305-319 [doi]
- PAC Bounds for Discounted MDPsTor Lattimore, Marcus Hutter. 320-334 [doi]
- Buy Low, Sell HighWouter M. Koolen, Vladimir Vovk. 335-349 [doi]
- Kernelization of Matrix Updates, When and How?Manfred K. Warmuth, Wojciech Kotlowski, Shuisheng Zhou. 350-364 [doi]
- Predictive Complexity and Generalized Entropy Rate of Stationary Ergodic ProcessesMrinal Kanti Ghosh, Satyadev Nandakumar. 365-379 [doi]