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» Experimental Design for Variable Selection in Data Bases
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CVPR
2009
IEEE
16 years 4 months ago
An Instance Selection Approach to Multiple Instance Learning
Multiple-instance Learning (MIL) is a new paradigm of supervised learning that deals with the classification of bags. Each bag is presented as a collection of instances from whi...
Zhouyu Fu (Australian National University), Antoni...
TVCG
2008
147views more  TVCG 2008»
14 years 9 months ago
Cerebral: Visualizing Multiple Experimental Conditions on a Graph with Biological Context
Systems biologists use interaction graphs to model the behavior of biological systems at the molecular level. In an iterative process, such biologists observe the reactions of livi...
Aaron Barsky, Tamara Munzner, Jennifer L. Gardy, R...
CODES
2008
IEEE
15 years 4 months ago
System-level mitigation of WID leakage power variability using body-bias islands
Adaptive Body Biasing (ABB) is a popularly used technique to mitigate the increasing impact of manufacturing process variations on leakage power dissipation. The efficacy of the ...
Siddharth Garg, Diana Marculescu
EKAW
2008
Springer
14 years 11 months ago
Towards a Rule-Based Matcher Selection
Abstract. The central problems w.r.t. interoperability and data integration issues in the Semantic Web are schema and ontology matching approaches. Today it takes an expert to dete...
Malgorzata Mochol, Anja Jentzsch
ADMA
2006
Springer
139views Data Mining» more  ADMA 2006»
15 years 3 months ago
Semantic Scoring Based on Small-World Phenomenon for Feature Selection in Text Mining
This paper proposes an effective scoring scheme for feature selection in Text Mining, using characteristics of Small-World Phenomenon on the semantic networks of documents. Our foc...
Chong Huang, YongHong Tian, Tiejun Huang, Wen Gao