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GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
15 years 1 months ago
Multi-step environment learning classifier systems applied to hyper-heuristics
Heuristic Algorithms (HA) are very widely used to tackle practical problems in operations research. They are simple, easy to understand and inspire confidence. Many of these HAs a...
Javier G. Marín-Blázquez, Sonia Schu...
SIGIR
2009
ACM
15 years 4 months ago
Personalized tag recommendation using graph-based ranking on multi-type interrelated objects
Social tagging is becoming increasingly popular in many Web 2.0 applications where users can annotate resources (e.g. Web pages) with arbitrary keywords (i.e. tags). A tag recomme...
Ziyu Guan, Jiajun Bu, Qiaozhu Mei, Chun Chen, Can ...
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ECCV
2006
Springer
15 years 11 months ago
Learning to Combine Bottom-Up and Top-Down Segmentation
Bottom-up segmentation based only on low-level cues is a notoriously difficult problem. This difficulty has lead to recent top-down segmentation algorithms that are based on class-...
Anat Levin, Yair Weiss
GECCO
2007
Springer
171views Optimization» more  GECCO 2007»
15 years 3 months ago
Toward a better understanding of rule initialisation and deletion
A number of heuristics have been used in Learning Classifier Systems to initialise parameters of new rules, to adjust fitness of parent rules when they generate offspring, and ...
Tim Kovacs, Larry Bull
GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
15 years 1 months ago
Estimating the destructiveness of crossover on binary tree representations
In some cases, evolutionary algorithms represent individuals as typical binary trees with n leaves and n-1 internal nodes. When designing a crossover operator for a particular rep...
Luke Sheneman, James A. Foster