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» Learning to Classify Texts Using Positive and Unlabeled Data
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ICML
2004
IEEE
14 years 8 months ago
Boosting margin based distance functions for clustering
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
CCIA
2009
Springer
13 years 8 months ago
Text Detection in Urban Scenes
Abstract. Text detection in urban scenes is a hard task due to the high variability of text appearance: different text fonts, changes in the point of view, or partial occlusion are...
Sergio Escalera, Xavier Baró, Jordi Vitri&a...
NIPS
2008
13 years 9 months ago
Exact Convex Confidence-Weighted Learning
Confidence-weighted (CW) learning [6], an online learning method for linear classifiers, maintains a Gaussian distributions over weight vectors, with a covariance matrix that repr...
Koby Crammer, Mark Dredze, Fernando Pereira
SIGIR
2008
ACM
13 years 7 months ago
Learning query intent from regularized click graphs
This work presents the use of click graphs in improving query intent classifiers, which are critical if vertical search and general-purpose search services are to be offered in a ...
Xiao Li, Ye-Yi Wang, Alex Acero
CVPR
2011
IEEE
13 years 3 months ago
Enforcing Similarity Constraints with Integer Programming for Better Scene Text Recognition
The recognition of text in everyday scenes is made difficult by viewing conditions, unusual fonts, and lack of linguistic context. Most methods integrate a priori appearance info...
David Smith, Jacqueline Feild, Eric Learned-Miller