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» Semi-supervised Learning from General Unlabeled Data
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BMCBI
2010
133views more  BMCBI 2010»
13 years 8 months ago
Improving de novo sequence assembly using machine learning and comparative genomics for overlap correction
Background: With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and appl...
Lance E. Palmer, Mathäus Dejori, Randall A. B...
AAAI
1994
13 years 9 months ago
The Ups and Downs of Lexical Acquisition
We have implemented an incremental lexical acquisition mechanism that learns the meanings of previously unknown words from the context in which they appear, as a part of the proce...
Peter M. Hastings, Steven L. Lytinen
KDD
2006
ACM
149views Data Mining» more  KDD 2006»
14 years 8 months ago
Regularized discriminant analysis for high dimensional, low sample size data
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
Jieping Ye, Tie Wang
NIPS
1990
13 years 9 months ago
Bumptrees for Efficient Function, Constraint and Classification Learning
A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. A...
Stephen M. Omohundro
KDD
2008
ACM
121views Data Mining» more  KDD 2008»
14 years 8 months ago
Reconstructing chemical reaction networks: data mining meets system identification
We present an approach to reconstructing chemical reaction networks from time series measurements of the concentrations of the molecules involved. Our solution strategy combines t...
Yong Ju Cho, Naren Ramakrishnan, Yang Cao