Spotlights 1
Cheeger Cuts and p-Spectral Clustering
Closed-form Supervised Dimensionality Reduction with Generalized Linear Models
Large-scale and larger-scale image search
Fitting a Graph to Vector Data
Introduction to Machine Learning
Distance Metric Learning for Kernel Machines
Deep Learning via Semi-Supervised Embedding
k-NN Regression Adapts to Local Intrinsic Dimension
One Shot Similarity Metric Learning for Action Recognition