Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
In this paper we present a framework for unsupervised segmentation of white matter fiber traces obtained from diffusion weighted MRI data. Fiber traces are compared pairwise to cre...
Anders Brun, Hans Knutsson, Hae-Jeong Park, Martha...
Modern data centers have a large number of components that must be monitored, including servers, switches/routers, and environmental control systems. This paper describes InteMon,...
Jimeng Sun, Evan Hoke, John D. Strunk, Gregory R. ...
This paper addresses the problem of learning similaritypreserving binary codes for efficient retrieval in large-scale image collections. We propose a simple and efficient altern...