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GECCO
2006
Springer
192views Optimization» more  GECCO 2006»
15 years 1 months ago
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...
TREC
2008
14 years 11 months ago
A Study of Adaptive Relevance Feedback - UIUC TREC 2008 Relevance Feedback Experiments
In this paper, we report our experiments in the TREC 2008 Relevance Feedback Track. Our main goal is to study a novel problem in feedback, i.e., optimization of the balance of the...
Yuanhua Lv, ChengXiang Zhai
GECCO
2008
Springer
123views Optimization» more  GECCO 2008»
14 years 10 months ago
MLS security policy evolution with genetic programming
In the early days a policy was a set of simple rules with a clear intuitive motivation that could be formalised to good effect. However the world is becoming much more complex. S...
Yow Tzu Lim, Pau-Chen Cheng, Pankaj Rohatgi, John ...
GECCO
2008
Springer
115views Optimization» more  GECCO 2008»
14 years 10 months ago
A genetic programming approach to business process mining
The aim of process mining is to identify and extract process patterns from data logs to reconstruct an overall process flowchart. As business processes become more and more comple...
Chris J. Turner, Ashutosh Tiwari, Jörn Mehnen
PR
2008
85views more  PR 2008»
14 years 9 months ago
Quadratic boosting
This paper presents a strategy to improve the AdaBoost algorithm with a quadratic combination of base classifiers. We observe that learning this combination is necessary to get be...
Thang V. Pham, Arnold W. M. Smeulders