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» Learning to rank with partially-labeled data
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AINA
2005
IEEE
15 years 5 months ago
iHITS: Extending HITS for Personal Interests Profiling
Ever since the boom of World Wide Web, profiling online users' interests has become an important task for content providers. The traditional approach involves manual entry of...
Ziming Zhuang
SIGIR
2005
ACM
15 years 5 months ago
Surrogate scoring for improved metasearch precision
We describe a method for improving the precision of metasearch results based upon scoring the visual features of documents' surrogate representations. These surrogate scores ...
Steven M. Beitzel, Eric C. Jensen, Ophir Frieder, ...
BMCBI
2010
97views more  BMCBI 2010»
14 years 11 months ago
Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on es...
Dirk Repsilber, Sabine Kern, Anna Telaar, Gerhard ...
ML
2008
ACM
248views Machine Learning» more  ML 2008»
14 years 11 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
ICCV
2011
IEEE
13 years 11 months ago
The Power of Comparative Reasoning
Rank correlation measures are known for their resilience to perturbations in numeric values and are widely used in many evaluation metrics. Such ordinal measures have rarely been ...
Jay Yagnik, Dennis Strelow, David Ross, Ruei-sung ...