: Tutorial on Practical Prediction Theory for Classification.
Savina Andonova Jaeger
: Generalization Bounds and Complexities Based on Sparsity and Clustering for Convex Combinations of Functions from Random Classes.
: Characterization of a Family of Algorithms for Generalized Discriminant Analysis on Undersampled Problems.
: Estimation of Non-Normalized Statistical Models by Score Matching.
: Quasi-Geodesic Neural Learning Algorithms Over the Orthogonal Group: A Tutorial.
: A Bayes Optimal Approach for Partitioning the Values of Categorical Attributes.
Robert G. Cowell
: Local Propagation in Conditional Gaussian Bayesian Networks.
Neil D. Lawrence
: Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models.
Rie Kubota Ando
, Tong Zhang
: A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data.
, Amnon Shashua
: Feature Selection for Unsupervised and Supervised Inference: The Emergence of Sparsity in a Weight-Based Approach.