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» Learning programs from noisy data
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NIPS
2003
13 years 8 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller
BMCBI
2010
155views more  BMCBI 2010»
13 years 7 months ago
A flexible R package for nonnegative matrix factorization
Background: Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face re...
Renaud Gaujoux, Cathal Seoighe
BMCBI
2006
140views more  BMCBI 2006»
13 years 7 months ago
SNP-PHAGE - High throughput SNP discovery pipeline
Background: Single nucleotide polymorphisms (SNPs) as defined here are single base sequence changes or short insertion/deletions between or within individuals of a given species. ...
Lakshmi K. Matukumalli, John J. Grefenstette, Davi...
BMCBI
2007
147views more  BMCBI 2007»
13 years 7 months ago
Hon-yaku: a biology-driven Bayesian methodology for identifying translation initiation sites in prokaryotes
Background: Computational prediction methods are currently used to identify genes in prokaryote genomes. However, identification of the correct translation initiation sites remain...
Yuko Makita, Michiel J. L. de Hoon, Antoine Danchi...
PROMISE
2010
13 years 2 months ago
Case-based reasoning vs parametric models for software quality optimization
Background: There are many data mining methods but few comparisons between them. For example, there are at least two ways to build quality optimizers, programs that find project o...
Adam Brady, Tim Menzies