We define a cluster to be characterized by regions of high density separated by regions that are sparse. By observing the downward closure property of density, the search for inte...
Alexei D. Miasnikov, Jayson E. Rome, Robert M. Har...
Shape comparisons of two groups of objects often have two goals: to create a classifier to separate the groups and to provide information that shows differences between classes. We...
Samson J. Timoner, Polina Golland, Ron Kikinis, Ma...
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...