• Learning Correction Grammars
  Lorenzo Carlucci, John Case, Sanjay Jain

• Occam's hammer
  Gilles Blanchard, Francois Fleuret

• Resampling-based confidence regions and multiple tests for a correlated random vector
  Sylvain Arlot, Gilles Blanchard, Etienne Roquain

• Mitotic Classes
  Sanjay Jain, Frank Stephan

• A Lower Bound for Agnostically Learning Disjunctions
  Adam Klivans, Alexander Sherstov

• Nonlinear Estimators and Tail Bounds for Dimension Reduction in l_1 Using Cauchy Random Projections
  Ping Li, Trevor Hastie, Kenneth Church

• The Loss Rank Principle for Model Selection
  Marcus Hutter

• Strategies for prediction under imperfect monitoring
  Shie Mannor, Gabor Lugosi, Gilles Stoltz

• Bounded Parameter Markov Decision Processes with Average Reward Criterion
  Ambuj Tewari, Peter Bartlett

• Mind Change Optimal Learning of Bayes Net Structure
  Oliver Schulte, Wei Luo, Russell Greiner

• On-line estimation with the multivariate Gaussian distribution
  Sanjoy Dasgupta, Daniel Hsu

• Generalised Entropies and Asymptotic Complexities of Languages
  Yuri Kalnishkan, Vladimir Vovk, Michael Vyugin

• Sparse density estimation with l1 penalties
  Florentina Bunea, Alexandre Tsybakov, Marten Wegkamp

• Learning Permutations with Exponential Weights
  David Helmbold, Manfred Warmuth

• How Good is a Kernel When Used as a Similarity Measure?
  Nathan Srebro

• Q-Learning and Function Approximation
  Francisco S. Melo, M. Isabel Ribeiro

• Suboptimality of Penalized Empirical Risk Minimization in Classification
  Guillaume Lecue

• U-Shaped, Iterative, and Iterative-with-Counter Learning
  Samuel Moelius, John Case

• An Efficient Re-scaled Perceptron Algorithm for Conic Systems
  Alexandre Belloni, Robert Freund, Santosh Vempala

• Transductive Rademacher complexity and its applications
  Ran El-Yaniv, Dmitry Pechyony

• Margin Based Active Learning
  Maria-Florina Balcan, Andrei Broder, Tong Zhang

• Regret to the Best vs. Regret to the Average
  Eyal Even-Dar, Michael Kearns, Yishay Mansour, Jennifer Wortman

• Online Learning with Prior Knowledge
  Elad Hazan, Nimrod Megiddo

• Observational Learning in Random Networks
  Julian Lorenz, Martin Marciniszyn, Angelika Steger

• Stability of k-Means Clustering
  David Pal, Shai Ben David, Hans Ulrich Simon

• Prediction by Categorical Features: Generalization Properties and Application to Feature Ranking
  Sivan Sabato, Shai Shalev-Shwartz

• Learning Large-Alphabet and Analog Circuits with Value Injection Queries
  Dana Angluin, James Aspnes, Jiang Chen, Lev Reyzin

• Robust Reductions from Ranking to Classification
  Maria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, Gregory B. Sorkin

• Learning Languages with Rational Kernels
  Corinna Cortes, Leonid Kontorovich, Mehryar Mohri

• Aggregation by exponential weighting and sharp oracle inequalities
  Arnak Dalalyan, Alexandre Tsybakov

• Teaching Dimension and the Complexity of Active Learning
  Steve Hanneke

• $\ell_1$ Regularization in Infinite Dimensional Feature Spaces
  Saharon Rosset, Grzegorz Swirszcz, Nathan Srebro, Ji Zhu

• Minimax Bounds for Active Learning
  Rui Castro, Robert Nowak

• Competing with stationary prediction strategies
  Vladimir Vovk

• Multi-View Regression via Canonical Correlation Analysis
  Sham Kakade, Dean Foster

• Multitask Learning with Expert Advice
  Jacob Abernethy, Peter Bartlett, Alexander Rakhlin

• Gaps in Support Vector Optimization
  Nikolas List, Don Hush, Clint Scovel, Ingo Steinwart

• Sketching Information Divergences
  Sudipto Guha, Piotr Indyk, Andrew McGregor

• Generalized SMO-style decomposition algorithms
  Nikolas List

• Improved Rates for the Stochastic Continuum-Armed Bandit Problem
  Peter Auer, Ronald Ortner, Csaba Szepesvari

• Learning Nested Halfspaces and Uphill Decision Trees
  Adam Kalai