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GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
13 years 11 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
ICML
2006
IEEE
14 years 8 months ago
Quadratic programming relaxations for metric labeling and Markov random field MAP estimation
Quadratic program relaxations are proposed as an alternative to linear program relaxations and tree reweighted belief propagation for the metric labeling or MAP estimation problem...
Pradeep D. Ravikumar, John D. Lafferty
MP
2002
84views more  MP 2002»
13 years 7 months ago
A decomposition procedure based on approximate Newton directions
The efficient solution of large-scale linear and nonlinear optimization problems may require exploiting any special structure in them in an efficient manner. We describe and analy...
Antonio J. Conejo, Francisco J. Nogales, Francisco...
PAMI
2011
13 years 2 months ago
Kernel Optimization in Discriminant Analysis
— Kernel mapping is one of the most used approaches to intrinsically derive nonlinear classifiers. The idea is to use a kernel function which maps the original nonlinearly separ...
Di You, Onur C. Hamsici, Aleix M. Martínez
TCBB
2011
13 years 2 months ago
Accurate Construction of Consensus Genetic Maps via Integer Linear Programming
—We study the problem of merging genetic maps, when the individual genetic maps are given as directed acyclic graphs. The computational problem is to build a consensus map, which...
Yonghui Wu, Timothy J. Close, Stefano Lonardi