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ICML
2004
IEEE
14 years 8 months ago
Training conditional random fields via gradient tree boosting
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...
ICML
2004
IEEE
14 years 8 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
EUROGP
2004
Springer
133views Optimization» more  EUROGP 2004»
14 years 28 days ago
Lymphoma Cancer Classification Using Genetic Programming with SNR Features
Lymphoma cancer classification with DNA microarray data is one of important problems in bioinformatics. Many machine learning techniques have been applied to the problem and produc...
Jin-Hyuk Hong, Sung-Bae Cho
GECCO
2004
Springer
137views Optimization» more  GECCO 2004»
14 years 27 days ago
Evolving Better Multiple Sequence Alignments
Aligning multiple DNA or protein sequences is a fundamental step in the analyses of phylogeny, homology and molecular structure. Heuristic algorithms are applied because optimal mu...
Luke Sheneman, James A. Foster
GECCO
2004
Springer
132views Optimization» more  GECCO 2004»
14 years 27 days ago
Optimizing Topology and Parameters of Gene Regulatory Network Models from Time-Series Experiments
Abstract. In this paper we address the problem of finding gene regulatory networks from experimental DNA microarray data. Different approaches to infer the dependencies of gene r...
Christian Spieth, Felix Streichert, Nora Speer, An...