We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we...
We propose an efficient algorithm to find the exact nearest neighbor based on the Euclidean distance for largescale computer vision problems. We embed data points nonlinearly on...
Skyline computation has many applications including multi-criteria decision making. In this paper, we study the problem of selecting k skyline points so that the number of points,...
K-Anonymity has been proposed as a mechanism for protecting privacy in microdata publishing, and numerous recoding "models" have been considered for achieving kanonymity...
Kristen LeFevre, David J. DeWitt, Raghu Ramakrishn...
After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in the training data. Particularl...