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CVPR
2012
IEEE
13 years 6 months ago
Learning hierarchical similarity metrics
Categories in multi-class data are often part of an underlying semantic taxonomy. Recent work in object classification has found interesting ways to use this taxonomy structure t...
Nakul Verma, Dhruv Mahajan, Sundararajan Sellamani...
ACL
2012
13 years 6 months ago
Joint Feature Selection in Distributed Stochastic Learning for Large-Scale Discriminative Training in SMT
With a few exceptions, discriminative training in statistical machine translation (SMT) has been content with tuning weights for large feature sets on small development data. Evid...
Patrick Simianer, Stefan Riezler, Chris Dyer
ICIP
2002
IEEE
16 years 5 months ago
Learning similarity space
In this study, we suggest a method to adapt an image retrieval system into a configurable one. Basically, original feature space of a content-based retrieval system is nonlinearly...
Abdurrahman Çarkacioglu, Fatos T. Yarman-Vu...
ICML
2003
IEEE
16 years 5 months ago
Learning Mixture Models with the Latent Maximum Entropy Principle
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin...
CVPR
2010
IEEE
16 years 12 days ago
Safety in Numbers: Learning Categories from Few Examples with Multi Model Knowledge Transfer
Learning object categories from small samples is a challenging problem, where machine learning tools can in general provide very few guarantees. Exploiting prior knowledge may be ...
Tatiana Tommasi, Francesco Orabona, Barbara Caputo