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CEC
2005
IEEE
15 years 3 months ago
Parallel evolutionary algorithms on graphics processing unit
Evolutionary Algorithms (EAs) are effective and robust methods for solving many practical problems such as feature selection, electrical circuits synthesis, and data mining. Howeve...
Man Leung Wong, Tien-Tsin Wong, Ka-Ling Fok
PKDD
2009
Springer
169views Data Mining» more  PKDD 2009»
15 years 4 months ago
Hybrid Least-Squares Algorithms for Approximate Policy Evaluation
The goal of approximate policy evaluation is to “best” represent a target value function according to a specific criterion. Temporal difference methods and Bellman residual m...
Jeffrey Johns, Marek Petrik, Sridhar Mahadevan
DMIN
2009
136views Data Mining» more  DMIN 2009»
14 years 7 months ago
Evaluating Algorithms for Concept Description
When performing concept description, models need to be evaluated both on accuracy and comprehensibility. A comprehensible concept description model should present the most importan...
Cecilia Sönströd, Ulf Johansson, Tuve L&...
KDD
2008
ACM
217views Data Mining» more  KDD 2008»
15 years 10 months ago
Stream prediction using a generative model based on frequent episodes in event sequences
This paper presents a new algorithm for sequence prediction over long categorical event streams. The input to the algorithm is a set of target event types whose occurrences we wis...
Srivatsan Laxman, Vikram Tankasali, Ryen W. White
ICDM
2006
IEEE
86views Data Mining» more  ICDM 2006»
15 years 3 months ago
Turning Clusters into Patterns: Rectangle-Based Discriminative Data Description
The ultimate goal of data mining is to extract knowledge from massive data. Knowledge is ideally represented as human-comprehensible patterns from which end-users can gain intuiti...
Byron J. Gao, Martin Ester