Efficient Learning of Sparse Conditional Random Fields for Supervised Sequence Labelling

Efficient Learning with Partially Observed Attributes

Efficient Matrix Completion with Gaussian Models

Efficient Minimization of Decomposable Submodular Functions

Efficient Multiclass Implementations of L1-Regularized Maximum Entropy

Efficient Multicore Collaborative Filtering

Efficient Online Learning for Opportunistic Spectrum Access

Efficient Online Learning via Randomized Rounding

Efficient Optimal Learning for Contextual Bandits

Efficient P2P Ensemble Learning with Linear Models on Fully Distributed Data

Efficient Probabilistic Inference with Partial Ranking Queries

Efficient Protocols for Distributed Classification and Optimization

Efficient Regression in Metric Spaces via Approximate Lipschitz Extension

Efficient Reinforcement Learning Using Recursive Least-Squares Methods

Efficient Tracking of Large Classes of Experts

Efficiently Learning Nonlinear Classifiers for Domain Specific Performance Measures

EigenGP: Gaussian processes with sparse data-dependent eigenfunctions

EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning

Eigenvectors for clustering: Unipartite, bipartite, and directed graph cases

Eignets for function approximation on manifolds