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» Preference-based learning to rank
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WWW
2011
ACM
15 years 7 days ago
Learning to re-rank: query-dependent image re-ranking using click data
Our objective is to improve the performance of keyword based image search engines by re-ranking their baseline results. To this end, we address three limitations of existing searc...
Vidit Jain, Manik Varma
ECCV
2010
Springer
15 years 10 months ago
Category Independent Object Proposals
We propose a category-independent method to produce a bag of regions and rank them, such that top-ranked regions are likely to be good segmentations of different objects. Our key ...
VLDB
1990
ACM
116views Database» more  VLDB 1990»
15 years 9 months ago
A Probabilistic Framework for Vague Queries and Imprecise Information in Databases
A probabilistic learning model for vague queries and missing or imprecise information in databases is described. Instead of retrieving only a set of answers, our approach yields a...
Norbert Fuhr
ECML
2006
Springer
15 years 9 months ago
A Discriminative Approach for the Retrieval of Images from Text Queries
This work proposes a new approach to the retrieval of images from text queries. Contrasting with previous work, this method relies on a discriminative model: the parameters are sel...
David Grangier, Florent Monay, Samy Bengio
137
Voted
ADMA
2005
Springer
144views Data Mining» more  ADMA 2005»
15 years 11 months ago
One Dependence Augmented Naive Bayes
In real-world data mining applications, an accurate ranking is same important to a accurate classification. Naive Bayes (simply NB) has been widely used in data mining as a simple...
Liangxiao Jiang, Harry Zhang, Zhihua Cai, Jiang Su