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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 5 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
13 years 11 months 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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