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» Learning and optimization using the clonal selection princip...
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ECML
2007
Springer
15 years 10 months ago
Optimizing Feature Sets for Structured Data
Choosing a suitable feature representation for structured data is a non-trivial task due to the vast number of potential candidates. Ideally, one would like to pick a small, but in...
Ulrich Rückert, Stefan Kramer
GECCO
2004
Springer
144views Optimization» more  GECCO 2004»
15 years 9 months ago
Feature Subset Selection, Class Separability, and Genetic Algorithms
Abstract. The performance of classification algorithms in machine learning is affected by the features used to describe the labeled examples presented to the inducers. Therefore,...
Erick Cantú-Paz
KDD
2004
ACM
158views Data Mining» more  KDD 2004»
16 years 4 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
155
Voted
IJCV
2011
264views more  IJCV 2011»
14 years 11 months ago
Cost-Sensitive Active Visual Category Learning
Abstract We present an active learning framework that predicts the tradeoff between the effort and information gain associated with a candidate image annotation, thereby ranking un...
Sudheendra Vijayanarasimhan, Kristen Grauman
ISMIS
1999
Springer
15 years 8 months ago
A Statistical Approach to Rule Selection in Semantic Query Optimisation
Semantic Query Optimisation makes use of the semantic knowledge of a database (rules) to perform query transformation. Rules are normally learned from former queries fired by the u...
Barry G. T. Lowden, Jerome Robinson