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ICDM
2010
IEEE
108views Data Mining» more  ICDM 2010»
13 years 3 months ago
Assessing Data Mining Results on Matrices with Randomization
Abstract--Randomization is a general technique for evaluating the significance of data analysis results. In randomizationbased significance testing, a result is considered to be in...
Markus Ojala
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 6 months ago
Scalable pseudo-likelihood estimation in hybrid random fields
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Antonino Freno, Edmondo Trentin, Marco Gori
FCT
2009
Springer
14 years 9 days ago
Competitive Group Testing and Learning Hidden Vertex Covers with Minimum Adaptivity
Suppose that we are given a set of n elements d of which are “defective”. A group test can check for any subset, called a pool, whether it contains a defective. It is well know...
Peter Damaschke, Azam Sheikh Muhammad
BMCBI
2007
226views more  BMCBI 2007»
13 years 5 months ago
MiRFinder: an improved approach and software implementation for genome-wide fast microRNA precursor scans
Background: MicroRNAs (miRNAs) are recognized as one of the most important families of noncoding RNAs that serve as important sequence-specific post-transcriptional regulators of ...
Ting-Hua Huang, Bin Fan, Max F. Rothschild, Zhi-Li...
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