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» Experimental Comparison of Feature Subset Selection Methods
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TIP
2010
155views more  TIP 2010»
15 years 4 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
SAT
2009
Springer
111views Hardware» more  SAT 2009»
16 years 22 days ago
Restart Strategy Selection Using Machine Learning Techniques
Abstract. Restart strategies are an important factor in the performance of conflict-driven Davis Putnam style SAT solvers. Selecting a good restart strategy for a problem instance...
Shai Haim, Toby Walsh
WWW
2006
ACM
16 years 6 months ago
Semantic WS-agreement partner selection
In a dynamic service oriented environment it is desirable for service consumers and providers to offer and obtain guarantees regarding their capabilities and requirements. WS-Agre...
Nicole Oldham, Kunal Verma, Amit P. Sheth, Farshad...
TRECVID
2007
15 years 7 months ago
NII-ISM, Japan at TRECVID 2007: High Level Feature Extraction
This paper reports our experiments on the concept detection task of TRECVID 2007. In these experiments, we have addressed two approaches which are selecting and fusing features and...
Duy-Dinh Le, Shin'ichi Satoh, Tomoko Matsui
EUROGP
2004
Springer
133views Optimization» more  EUROGP 2004»
15 years 11 months ago
Lymphoma Cancer Classification Using Genetic Programming with SNR Features
Lymphoma cancer classification with DNA microarray data is one of important problems in bioinformatics. Many machine learning techniques have been applied to the problem and produc...
Jin-Hyuk Hong, Sung-Bae Cho