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» An Instance Selection Approach to Multiple Instance Learning
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CSB
2004
IEEE
149views Bioinformatics» more  CSB 2004»
14 years 18 days ago
Weighting Features to Recognize 3D Patterns of Electron Density in X-Ray Protein Crystallography
Feature selection and weighting are central problems in pattern recognition and instance-based learning. In this work, we discuss the challenges of constructing and weighting feat...
Kreshna Gopal, Tod D. Romo, James C. Sacchettini, ...
CP
2004
Springer
14 years 2 months ago
Heuristic Selection for Stochastic Search Optimization: Modeling Solution Quality by Extreme Value Theory
The success of stochastic algorithms is often due to their ability to effectively amplify the performance of search heuristics. This is certainly the case with stochastic sampling ...
Vincent A. Cicirello, Stephen F. Smith
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
14 years 9 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil
EVOW
2005
Springer
14 years 2 months ago
Choosing the Fittest Subset of Low Level Heuristics in a Hyperheuristic Framework
A hyperheuristic is a high level procedure which searches over a space of low level heuristics rather than directly over the space of problem solutions. The sequence of low level h...
Konstantin Chakhlevitch, Peter I. Cowling
GECCO
2004
Springer
107views Optimization» more  GECCO 2004»
14 years 2 months ago
Multiple Species Weighted Voting - A Genetics-Based Machine Learning System
Multiple Species Weighted Voting (MSWV) is a genetics-based machine learning (GBML) system with relatively few parameters that combines N two-class classifiers into an N -class cla...
Alexander F. Tulai, Franz Oppacher