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ICML
2006
IEEE
14 years 8 months ago
The support vector decomposition machine
In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
Francisco Pereira, Geoffrey J. Gordon
INTERSPEECH
2010
13 years 2 months ago
Reduction of broadband noise in speech signals by multilinear subspace analysis
A new noise reduction method for speech signals is proposed in this paper. The method is based upon the N-mode singular value decomposition algorithm, which exploits the multiline...
Yusuke Sato, Tetsuya Hoya, Hovagim Bakardjian, And...
TPDS
1998
108views more  TPDS 1998»
13 years 7 months ago
Critical Path Profiling of Message Passing and Shared-Memory Programs
—In this paper, we introduce a runtime, nontrace-based algorithm to compute the critical path profile of the execution of message passing and shared-memory parallel programs. Our...
Jeffrey K. Hollingsworth
BMCBI
2008
95views more  BMCBI 2008»
13 years 7 months ago
Unsupervised reduction of random noise in complex data by a row-specific, sorted principal component-guided method
Background: Large biological data sets, such as expression profiles, benefit from reduction of random noise. Principal component (PC) analysis has been used for this purpose, but ...
Joseph W. Foley, Fumiaki Katagiri
ICPP
1999
IEEE
13 years 11 months ago
Producer-Push - A Protocol Enhancement to Page-Based Software Distributed Shared Memory Systems
This paper describes a technique called producer-push that enhances the performance of a page-based software distributed shared memory system. Shared data, in software DSM systems...
Sven Karlsson, Mats Brorsson