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JMLR
2010
147views more  JMLR 2010»
15 years 2 months ago
Spectral Regularization Algorithms for Learning Large Incomplete Matrices
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...
Rahul Mazumder, Trevor Hastie, Robert Tibshirani
CVPR
2012
IEEE
13 years 9 months ago
A fast nearest neighbor search algorithm by nonlinear embedding
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...
Yoonho Hwang, Bohyung Han, Hee-Kap Ahn
ICDE
2007
IEEE
140views Database» more  ICDE 2007»
16 years 8 months ago
Selecting Stars: The k Most Representative Skyline Operator
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,...
Xuemin Lin, Yidong Yuan, Qing Zhang, Ying Zhang
ICDE
2006
IEEE
176views Database» more  ICDE 2006»
16 years 8 months ago
Mondrian Multidimensional K-Anonymity
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...
ICML
2008
IEEE
16 years 8 months ago
Learning to classify with missing and corrupted features
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...
Ofer Dekel, Ohad Shamir