Stat-Ml
Hybrid Generative/Discriminative Learning for Automatic Image Annotation
Sparse estimation via nonconcave penalized likelihood in a factor analysis model
Dependence Maximizing Temporal Alignment via Squared-Loss Mutual Information
Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression
Active Bayesian Optimization: Minimizing Minimizer Entropy
An Online Learning-based Framework for Tracking
On the Difficulty of Nearest Neighbor Search
The threshold EM algorithm for parameter learning in bayesian network with incomplete data
Kernels on Sample Sets via Nonparametric Divergence Estimates
Transductive Rademacher Complexity and its Applications
Bounded Planning in Passive POMDPs
Adaptive Policies for Sequential Sampling under Incomplete Information and a Cost Constraint
A Stochastic Model for Collaborative Recommendation
Risk Bounds for CART Classifiers under a Margin Condition
Sparse Empirical Bayes Analysis (SEBA)
Optimal learning rates for Kernel Conjugate Gradient regression
Query Learning with Exponential Query Costs
PADDLE: Proximal Algorithm for Dual Dictionaries LEarning
Taking Advantage of Sparsity in Multi-Task Learning
Kernels for Measures Defined on the Gram Matrix of their Support
The Lasso under Heteroscedasticity
Information-theoretic lower bounds on the oracle complexity of stochastic convex optimization
