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JMLR
2011
148views more  JMLR 2011»
13 years 2 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
COLT
2005
Springer
14 years 1 months ago
Leaving the Span
We discuss a simple sparse linear problem that is hard to learn with any algorithm that uses a linear combination of the training instances as its weight vector. The hardness holds...
Manfred K. Warmuth, S. V. N. Vishwanathan
SIGIR
2012
ACM
11 years 10 months ago
Boosting multi-kernel locality-sensitive hashing for scalable image retrieval
Similarity search is a key challenge for multimedia retrieval applications where data are usually represented in high-dimensional space. Among various algorithms proposed for simi...
Hao Xia, Pengcheng Wu, Steven C. H. Hoi, Rong Jin
CVPR
2004
IEEE
14 years 9 months ago
Feature Selection for Classifying High-Dimensional Numerical Data
Classifying high-dimensional numerical data is a very challenging problem. In high dimensional feature spaces, the performance of supervised learning methods suffer from the curse...
Yimin Wu, Aidong Zhang
TIP
2008
287views more  TIP 2008»
13 years 7 months ago
3-D Object Recognition Using 2-D Views
We consider the problem of recognizing 3-D objects from 2-D images using geometric models and assuming different viewing angles and positions. Our goal is to recognize and localize...
Wenjing Li, George Bebis, Nikolaos G. Bourbakis