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IPPS
2002
IEEE
14 years 9 days ago
High-Performance Parallel and Distributed Computing for the BMI Eigenvalue Problem
The BMI Eigenvalue Problem is one of optimization problems and is to minimize the greatest eigenvalue of a bilinear matrix function. This paper proposes a parallel algorithm to co...
Kento Aida, Yoshiaki Futakata, Shinji Hara

Publication
197views
12 years 3 months ago
Convex non-negative matrix factorization for massive datasets
Non-negative matrix factorization (NMF) has become a standard tool in data mining, information retrieval, and signal processing. It is used to factorize a non-negative data matrix ...
C. Thurau, K. Kersting, M. Wahabzada, and C. Bauck...
ICMLA
2008
13 years 8 months ago
An Improved Generalized Discriminant Analysis for Large-Scale Data Set
In order to overcome the computation and storage problem for large-scale data set, an efficient iterative method of Generalized Discriminant Analysis is proposed. Because sample v...
Weiya Shi, Yue-Fei Guo, Cheng Jin, Xiangyang Xue
TIT
2010
107views Education» more  TIT 2010»
13 years 2 months ago
Information inequalities for joint distributions, with interpretations and applications
Upper and lower bounds are obtained for the joint entropy of a collection of random variables in terms of an arbitrary collection of subset joint entropies. These inequalities gene...
Mokshay M. Madiman, Prasad Tetali
NIPS
2008
13 years 8 months ago
Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform
Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
Guangzhi Cao, Charles A. Bouman