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» Learning to rank with partially-labeled data
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AAAI
2012
13 years 2 months ago
Discovering Constraints for Inductive Process Modeling
Scientists use two forms of knowledge in the construction of explanatory models: generalized entities and processes that relate them; and constraints that specify acceptable combi...
Ljupco Todorovski, Will Bridewell, Pat Langley
KDD
2010
ACM
289views Data Mining» more  KDD 2010»
14 years 9 months ago
Exploitation and exploration in a performance based contextual advertising system
The dynamic marketplace in online advertising calls for ranking systems that are optimized to consistently promote and capitalize better performing ads. The streaming nature of on...
Wei Li 0010, Xuerui Wang, Ruofei Zhang, Ying Cui, ...
WSDM
2010
ACM
214views Data Mining» more  WSDM 2010»
15 years 9 months ago
Pairwise Interaction Tensor Factorization for Personalized Tag Recommendation
Tagging plays an important role in many recent websites. Recommender systems can help to suggest a user the tags he might want to use for tagging a specific item. Factorization mo...
Steffen Rendle, Lars Schmidt-Thieme
CVPR
2012
IEEE
13 years 2 months ago
Fixed-rank representation for unsupervised visual learning
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...
78
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KDD
2005
ACM
130views Data Mining» more  KDD 2005»
16 years 5 days ago
Simple and effective visual models for gene expression cancer diagnostics
In the paper we show that diagnostic classes in cancer gene expression data sets, which most often include thousands of features (genes), may be effectively separated with simple ...
Gregor Leban, Minca Mramor, Ivan Bratko, Blaz Zupa...