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» Learning on the Test Data: Leveraging Unseen Features
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BMCBI
2010
179views more  BMCBI 2010»
13 years 9 months ago
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
Zhuhong You, Zheng Yin, Kyungsook Han, De-Shuang H...
RECOMB
2005
Springer
14 years 9 months ago
The Factor Graph Network Model for Biological Systems
Abstract. We introduce an extended computational framework for studying biological systems. Our approach combines formalization of existing qualitative models that are in wide but ...
Irit Gat-Viks, Amos Tanay, Daniela Raijman, Ron Sh...
KDD
2009
ACM
173views Data Mining» more  KDD 2009»
14 years 1 months ago
Malware detection using statistical analysis of byte-level file content
Commercial anti-virus software are unable to provide protection against newly launched (a.k.a “zero-day”) malware. In this paper, we propose a novel malware detection techniqu...
S. Momina Tabish, M. Zubair Shafiq, Muddassar Faro...
ICONIP
2007
13 years 10 months ago
Using Image Stimuli to Drive fMRI Analysis
We introduce a new unsupervised fMRI analysis method based on Kernel Canonical Correlation Analysis which differs from the class of supervised learning methods that are increasing...
David R. Hardoon, Janaina Mourão Miranda, M...
NAACL
2010
13 years 7 months ago
Minimally-Supervised Extraction of Entities from Text Advertisements
Extraction of entities from ad creatives is an important problem that can benefit many computational advertising tasks. Supervised and semi-supervised solutions rely on labeled da...
Sameer Singh, Dustin Hillard, Chris Leggetter