Abstract is missing.
- Fast and Optimal Prediction on a Labeled TreeNicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale. [doi]
- Hybrid Stochastic-Adversarial On-line LearningAlessandro Lazaric, Rémi Munos. [doi]
- Beating the Adaptive Bandit with High ProbabilityJacob Abernethy, Alexander Rakhlin. [doi]
- Sparse Regression Learning by Aggregation and Langevin Monte-CarloArnak S. Dalalyan, Alexandre B. Tsybakov. [doi]
- Tighter Bounds for Multi-Armed Bandits with Expert AdviceH. Brendan McMahan, Matthew J. Streeter. [doi]
- Online Multi-task Learning with Hard ConstraintsGábor Lugosi, Omiros Papaspiliopoulos, Gilles Stoltz. [doi]
- An Efficient Bandit Algorithm for sqrt(T) Regret in Online Multiclass Prediction?Jacob Abernethy, Alexander Rakhlin. [doi]
- Consistent Partial IdentificationSanjay Jain, Frank Stephan. [doi]
- Better Guarantees for Sparsest Cut ClusteringMaria-Florina Balcan. [doi]
- Adaptive Rates of Convergence in Active LearningSteve Hanneke. [doi]
- Combinatorial BanditsNicolò Cesa-Bianchi, Gábor Lugosi. [doi]
- Learnability and Stability in the General Learning SettingShai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan. [doi]
- Homogeneous Multi-Instance Learning with Arbitrary DependenceSivan Sabato, Naftali Tishby. [doi]
- Empirical Bernstein Bounds and Sample-Variance PenalizationAndreas Maurer, Massimiliano Pontil. [doi]
- Robustness of EvolvabilityVitaly Feldman. [doi]
- A Spectral Algorithm for Learning Hidden Markov ModelsDaniel Hsu, Sham M. Kakade, Tong Zhang. [doi]
- Minimax Policies for Adversarial and Stochastic BanditsJean-Yves Audibert, Sébastien Bubeck. [doi]
- Linear Classifiers are Nearly Optimal When Hidden Variables Have Diverse EffectNader H. Bshouty, Philip M. Long. [doi]
- A Note on Learning with Integral OperatorsLorenzo Rosasco, Mikhail Belkin, Ernesto De Vito. [doi]
- Generalised Pinsker InequalitiesMark D. Reid, Robert C. Williamson. [doi]
- Reliable Agnostic LearningAdam Tauman Kalai, Varun Kanade, Yishay Mansour. [doi]
- Active Learning for Smooth ProblemsEric Friedman. [doi]
- Learning Convex Bodies is HardLuis Rademacher, Navin Goyal. [doi]
- The Isotron Algorithm: High-Dimensional Isotonic RegressionAdam Tauman Kalai, Ravi Sastry. [doi]
- Predicting the Labelling of a Graph via Minimum p -Seminorm InterpolationMark Herbster, Guy Lever. [doi]
- Optimal Algorithms for the Coin Weighing Problem with a Spring ScaleNader H. Bshouty. [doi]
- SVM-Optimization and Steepest-Descent Line SearchHans-Ulrich Simon, Nikolas List. [doi]
- Finding Low Error ClusteringsMaria-Florina Balcan, Mark Braverman. [doi]
- A Stochastic View of Optimal Regret through Minimax DualityJacob Abernethy, Alekh Agarwal, Peter L. Bartlett, Alexander Rakhlin. [doi]
- Optimal Rates for Regularized Least Squares RegressionIngo Steinwart, Don R. Hush, Clint Scovel. [doi]
- The K-armed Dueling Bandits ProblemYisong Yue, Josef Broder, Robert Kleinberg, Thorsten Joachims. [doi]
- Stochastic Convex OptimizationShai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan. [doi]
- Complexity of Teaching by a Restricted Number of ExamplesHayato Kobayashi, Ayumi Shinohara. [doi]
- Minimax Games with BanditsJacob Abernethy, Manfred K. Warmuth. [doi]
- The Complexity of Improperly Learning Large Margin HalfspacesShai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan. [doi]
- Taking Advantage of Sparsity in Multi-Task LearningKarim Lounici, Massimiliano Pontil, Alexandre B. Tsybakov, Sara A. van de Geer. [doi]
- Domain Adaptation: Learning Bounds and AlgorithmsYishay Mansour, Mehryar Mohri, Afshin Rostamizadeh. [doi]
- Generalization Bounds for Learning the Kernel ProblemYiming Ying, Colin Campbell. [doi]
- Vox Populi: Collecting High-Quality Labels from a CrowdOfer Dekel, Ohad Shamir. [doi]
- New Results for Random Walk LearningJeffrey Jackson, Karl Wimmer. [doi]
- Agnostic Online LearningShai Ben-David, Dávid Pál, Shai Shalev-Shwartz. [doi]
- Escaping the Curse of Dimensionality with a Tree-based RegressorSamory Kpotufe. [doi]
- On the Sample Complexity of Learning Smooth Cuts on a ManifoldHariharan Narayanan, Partha Niyogi. [doi]