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» Learning and Generalization with the Information Bottleneck
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KDD
2004
ACM
139views Data Mining» more  KDD 2004»
16 years 7 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
ITICSE
2009
ACM
16 years 1 months ago
Relating research and teaching: learning from experiences and beliefs
The relationship between research and teaching has possible benefits and inherent tensions. Exploring the potentially beneficial relationship is of interest and possible value to ...
Su White, Alastair Irons
IUI
2003
ACM
15 years 12 months ago
Lessons learned in modeling schizophrenic and depressed responsive virtual humans for training
This paper describes lessons learned in developing the linguistic, cognitive, emotional, and gestural models underlying virtual human behavior in a training application designed t...
Robert C. Hubal, Geoffrey A. Frank, Curry I. Guinn
CORR
2008
Springer
173views Education» more  CORR 2008»
15 years 6 months ago
Decomposition Principles and Online Learning in Cross-Layer Optimization for Delay-Sensitive Applications
In this paper, we propose a general cross-layer optimization framework in which we explicitly consider both the heterogeneous and dynamically changing characteristics of delay-sens...
Fangwen Fu, Mihaela van der Schaar
BMCBI
2006
151views more  BMCBI 2006»
15 years 6 months ago
Machine learning and word sense disambiguation in the biomedical domain: design and evaluation issues
Background: Word sense disambiguation (WSD) is critical in the biomedical domain for improving the precision of natural language processing (NLP), text mining, and information ret...
Hua Xu, Marianthi Markatou, Rositsa Dimova, Hongfa...