Elastic-Net Regularization in Learning Theory

Empirical Bernstein Bounds and Sample Variance Penalization

Empirical Normalization for Quadratic Discriminant Analysis and Classifying Cancer Subtypes

Ensemble Models with Trees and Rules

Entropy inference and the James-Stein estimator, with application to nonlinear gene association networks

Entropy Search for Information-Efficient Global Optimization

Entropy-Based Search Algorithm for Experimental Design

EP-GIG Priors and Applications in Bayesian Sparse Learning

Escaping the curse of dimensionality with a tree-based regressor

Estimated VC dimension for risk bounds

Estimating $β$-mixing coefficients

Estimating Networks With Jumps

Estimating Subagging by cross-validation

Estimating time-varying networks

Estimation And Selection Via Absolute Penalized Convex Minimization And Its Multistage Adaptive Applications

Estimation of causal orders in a linear non-Gaussian acyclic model: a method robust against latent confounders

Estimation of low-rank tensors via convex optimization

Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs

Estimation of scale functions to model heteroscedasticity by support vector machines

Euclidean Distances, soft and spectral Clustering on Weighted Graphs