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» Cost-Sensitive Learning of SVM for Ranking
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ICML
2010
IEEE
13 years 6 months ago
Metric Learning to Rank
We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that ...
Brian McFee, Gert R. G. Lanckriet
ISBI
2009
IEEE
14 years 9 days ago
Bridging the Semantic Gap Using Ranking Svm for Image Retrieval
One of the main challenges for Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings between the high-level semantic concepts and the low-level visual features in...
Haiying Guan, Sameer Antani, L. Rodney Long, Georg...
CVPR
2007
IEEE
14 years 7 months ago
Modeling Appearances with Low-Rank SVM
Several authors have noticed that the common representation of images as vectors is sub-optimal. The process of vectorization eliminates spatial relations between some of the near...
Lior Wolf, Hueihan Jhuang, Tamir Hazan
KDD
2006
ACM
191views Data Mining» more  KDD 2006»
14 years 5 months ago
Beyond classification and ranking: constrained optimization of the ROI
Classification has been commonly used in many data mining projects in the financial service industry. For instance, to predict collectability of accounts receivable, a binary clas...
Lian Yan, Patrick Baldasare
NAACL
2010
13 years 3 months ago
Learning Dense Models of Query Similarity from User Click Logs
The goal of this work is to integrate query similarity metrics as features into a dense model that can be trained on large amounts of query log data, in order to rank query rewrit...
Fabio De Bona, Stefan Riezler, Keith Hall, Massimi...