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» Predicting good probabilities with supervised learning
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JMLR
2010
179views more  JMLR 2010»
13 years 1 months ago
PAC-Bayesian Analysis of Co-clustering and Beyond
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...
Yevgeny Seldin, Naftali Tishby
BMCBI
2005
155views more  BMCBI 2005»
13 years 6 months ago
Mining protein function from text using term-based support vector machines
Background: Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We...
Simon B. Rice, Goran Nenadic, Benjamin J. Stapley
TSE
2002
157views more  TSE 2002»
13 years 5 months ago
Assessing the Applicability of Fault-Proneness Models Across Object-Oriented Software Projects
A number of papers have investigated the relationships between design metrics and the detection of faults in object-oriented software. Several of these studies have shown that suc...
Lionel C. Briand, Walcélio L. Melo, Jü...
BMCBI
2010
111views more  BMCBI 2010»
13 years 6 months ago
Protein sequences classification by means of feature extraction with substitution matrices
Background: This paper deals with the preprocessing of protein sequences for supervised classification. Motif extraction is one way to address that task. It has been largely used ...
Rabie Saidi, Mondher Maddouri, Engelbert Mephu Ngu...
FOCS
1989
IEEE
13 years 10 months ago
Constant Depth Circuits, Fourier Transform, and Learnability
In this paper, Boolean functions in ,4C0 are studied using harmonic analysis on the cube. The main result is that an ACO Boolean function has almost all of its “power spectrum”...
Nathan Linial, Yishay Mansour, Noam Nisan