We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Three techniques: Principal Component Analy...
We propose a new algorithm for independent component and independent subspace analysis problems. This algorithm uses a contrast based on the Schweizer-Wolff measure of pairwise de...
GEGICK, MICHAEL CHARLES. Predicting Attack-prone Components with Source Code Static Analyzers. (Under the direction of Laurie Williams). No single vulnerability detection techniqu...
This manuscript proposes a retrieval system for fMRI brain images. Our goal is to find a similaritymetric to enable us to support queries for “similar tasks” for retrieval on...
Bing Bai, Paul B. Kantor, Ali Shokoufandeh, Debora...
We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...