Abstract is missing.
- Property Testing: A Learning Theory PerspectiveDana Ron. 1-2 [doi]
- Spectral Algorithms for Learning and ClusteringSantosh Vempala. 3-4 [doi]
- Minimax Bounds for Active LearningRui Castro, Robert D. Nowak. 5-19 [doi]
- Stability of ::::k:::: -Means ClusteringShai Ben-David, Dávid Pál, Hans-Ulrich Simon. 20-34 [doi]
- Margin Based Active LearningMaria-Florina Balcan, Andrei Z. Broder, Tong Zhang. 35-50 [doi]
- Learning Large-Alphabet and Analog Circuits with Value Injection QueriesDana Angluin, James Aspnes, Jiang Chen, Lev Reyzin. 51-65 [doi]
- Teaching Dimension and the Complexity of Active LearningSteve Hanneke. 66-81 [doi]
- Multi-view Regression Via Canonical Correlation AnalysisSham M. Kakade, Dean P. Foster. 82-96 [doi]
- Aggregation by Exponential Weighting and Sharp Oracle InequalitiesArnak S. Dalalyan, Alexandre B. Tsybakov. 97-111 [doi]
- Occam s HammerGilles Blanchard, François Fleuret. 112-126 [doi]
- Resampling-Based Confidence Regions and Multiple Tests for a Correlated Random VectorSylvain Arlot, Gilles Blanchard, Étienne Roquain. 127-141 [doi]
- Suboptimality of Penalized Empirical Risk Minimization in ClassificationGuillaume Lecué. 142-156 [doi]
- Transductive Rademacher Complexity and Its ApplicationsRan El-Yaniv, Dmitry Pechyony. 157-171 [doi]
- U-Shaped, Iterative, and Iterative-with-Counter LearningJohn Case, Samuel E. Moelius. 172-186 [doi]
- Mind Change Optimal Learning of Bayes Net StructureOliver Schulte, Wei Luo, Russell Greiner. 187-202 [doi]
- Learning Correction GrammarsLorenzo Carlucci, John Case, Sanjay Jain. 203-217 [doi]
- Mitotic ClassesSanjay Jain, Frank Stephan. 218-232 [doi]
- Regret to the Best vs. Regret to the AverageEyal Even-Dar, Michael J. Kearns, Yishay Mansour, Jennifer Wortman. 233-247 [doi]
- Strategies for Prediction Under Imperfect MonitoringGábor Lugosi, Shie Mannor, Gilles Stoltz. 248-262 [doi]
- Bounded Parameter Markov Decision Processes with Average Reward CriterionAmbuj Tewari, Peter L. Bartlett. 263-277 [doi]
- On-Line Estimation with the Multivariate Gaussian DistributionSanjoy Dasgupta, Daniel Hsu. 278-292 [doi]
- Generalised Entropy and Asymptotic Complexities of LanguagesYuri Kalnishkan, Vladimir Vovk, Michael V. Vyugin. 293-307 [doi]
- ::::Q:::: -Learning with Linear Function ApproximationFrancisco S. Melo, M. Isabel Ribeiro. 308-322 [doi]
- How Good Is a Kernel When Used as a Similarity Measure?Nathan Srebro. 323-335 [doi]
- Gaps in Support Vector OptimizationNikolas List, Don R. Hush, Clint Scovel, Ingo Steinwart. 336-348 [doi]
- Learning Languages with Rational KernelsCorinna Cortes, Leonid Kontorovich, Mehryar Mohri. 349-364 [doi]
- Generalized SMO-Style Decomposition AlgorithmsNikolas List. 365-377 [doi]
- Learning Nested Halfspaces and Uphill Decision TreesAdam Tauman Kalai. 378-392 [doi]
- An Efficient Re-scaled Perceptron Algorithm for Conic SystemsAlexandre Belloni, Robert M. Freund, Santosh Vempala. 393-408 [doi]
- A Lower Bound for Agnostically Learning DisjunctionsAdam R. Klivans, Alexander A. Sherstov. 409-423 [doi]
- Sketching Information DivergencesSudipto Guha, Piotr Indyk, Andrew McGregor. 424-438 [doi]
- Competing with Stationary Prediction StrategiesVladimir Vovk. 439-453 [doi]
- Improved Rates for the Stochastic Continuum-Armed Bandit ProblemPeter Auer, Ronald Ortner, Csaba Szepesvári. 454-468 [doi]
- Learning Permutations with Exponential WeightsDavid P. Helmbold, Manfred K. Warmuth. 469-483 [doi]
- Multitask Learning with Expert AdviceJacob Abernethy, Peter L. Bartlett, Alexander Rakhlin. 484-498 [doi]
- Online Learning with Prior KnowledgeElad Hazan, Nimrod Megiddo. 499-513 [doi]
- Nonlinear Estimators and Tail Bounds for Dimension Reduction in ::::l:::: ::1:: Using Cauchy Random ProjectionsPing Li, Trevor Hastie, Kenneth Ward Church. 514-529 [doi]
- Sparse Density Estimation with ::::l::::::1:: PenaltiesFlorentina Bunea, Alexandre B. Tsybakov, Marten H. Wegkamp. 530-543 [doi]
- ::::l::::::1:: Regularization in Infinite Dimensional Feature SpacesSaharon Rosset, Grzegorz Swirszcz, Nathan Srebro, Ji Zhu. 544-558 [doi]
- Prediction by Categorical Features: Generalization Properties and Application to Feature RankingSivan Sabato, Shai Shalev-Shwartz. 559-573 [doi]
- Observational Learning in Random NetworksJulian Lorenz, Martin Marciniszyn, Angelika Steger. 574-588 [doi]
- The Loss Rank Principle for Model SelectionMarcus Hutter. 589-603 [doi]
- Robust Reductions from Ranking to ClassificationMaria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, Gregory B. Sorkin. 604-619 [doi]
- Rademacher Margin ComplexityLiwei Wang, Jufu Feng. 620-621 [doi]
- Open Problems in Efficient Semi-supervised PAC LearningAvrim Blum, Maria-Florina Balcan. 622-624 [doi]
- Resource-Bounded Information Gathering for Correlation ClusteringPallika Kanani, Andrew McCallum. 625-627 [doi]
- Are There Local Maxima in the Infinite-Sample Likelihood of Gaussian Mixture Estimation?Nathan Srebro. 628-629 [doi]
- When Is There a Free Matrix Lunch?Manfred K. Warmuth. 630-632 [doi]