The growing usage of statistical shape analysis in medical imaging calls for effective methods for highly accurate shape correspondence. This paper presents a novel landmark-based ...
Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameters learning can take two different approaches: ge...
Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwi...
Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
Learning from structured data is becoming increasingly important. However, most prior work on kernel methods has focused on learning from attribute-value data. Only recently, rese...
Adam Kowalczyk, Alex J. Smola, Peter A. Flach, Tho...
Interaction patterns and pattern languages have been discussed for years in HCI literature yet there have been few empirical studies conducted. We describe aIRPLane: An Informatio...