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» A general algorithm for data dependence analysis
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PPOPP
1999
ACM
15 years 7 months ago
Automatic Parallelization of Divide and Conquer Algorithms
Divide and conquer algorithms are a good match for modern parallel machines: they tend to have large amounts of inherent parallelism and they work well with caches and deep memory...
Radu Rugina, Martin C. Rinard
137
Voted
KDD
2010
ACM
246views Data Mining» more  KDD 2010»
15 years 1 months ago
Latent aspect rating analysis on review text data: a rating regression approach
In this paper, we define and study a new opinionated text data analysis problem called Latent Aspect Rating Analysis (LARA), which aims at analyzing opinions expressed about an e...
Hongning Wang, Yue Lu, Chengxiang Zhai
CIBCB
2009
IEEE
15 years 4 months ago
A framework for the application of decision trees to the analysis of SNPs data
Data mining is the analysis of experimental datasets to extract trends and relationships that can be meaningful for the user. In genetic studies these techniques have revealed inte...
Linda Fiaschi, Jonathan M. Garibaldi, Natalio Kras...
139
Voted
BMCBI
2006
126views more  BMCBI 2006»
15 years 3 months ago
A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data
Background: As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heteroge...
Zizhen Yao, Walter L. Ruzzo
ICASSP
2010
IEEE
14 years 9 months ago
Temporally constrained SCA with applications to EEG data
In this paper we propose an iterative algorithm for solving the problem of extracting a sparse source signal when a reference signal for the desired source signal is available. In...
Nasser Mourad, James P. Reilly, Gary Hasey, Duncan...