Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
With the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. Strangely, despite extensive ...
In robotics, the idea of human and robot interaction is receiving a lot of attention lately. In this paper, we describe a multi-modal system for generating a map of the environment...
When developing semantic applications, the construction of ontologies is a crucial part. We are developing a semiautomatic ontology construction approach, OntoCase, relying on ont...
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...