Stat-Ml
Estimating Subagging by cross-validation
Positive Definite Kernels in Machine Learning
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
Structured Variable Selection with Sparsity-Inducing Norms
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
Asymptotic Synchronization for Finite-State Sources
Effect of Hyper-Parameter Optimization on the Deep Learning Model Proposed for Distributed Attack Detection in Internet of Things Environment
Estimating time-varying networks
Manifold Elastic Net: A Unified Framework for Sparse Dimension Reduction
Support union recovery in high-dimensional multivariate regression
A Stochastic View of Optimal Regret through Minimax Duality
Dirichlet Process Mixtures of Generalized Linear Models
Empirical Bernstein Bounds and Sample Variance Penalization
Geometry of the restricted Boltzmann machine
Information, Divergence and Risk for Binary Experiments
Lasso type classifiers with a reject option
Minimum Probability Flow Learning
PAC-Bayesian Bounds for Randomized Empirical Risk Minimizers
Practical Robust Estimators for the Imprecise Dirichlet Model
Rumors in a Network: Whos the Culprit?
Sparse Causal Discovery in Multivariate Time Series
Sparse Convolved Multiple Output Gaussian Processes
