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» On learning with dissimilarity functions
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ICML
2000
IEEE
16 years 7 months ago
A Nonparametric Approach to Noisy and Costly Optimization
This paper describes Pairwise Bisection: a nonparametric approach to optimizing a noisy function with few function evaluations. The algorithm uses nonparametric reasoning about si...
Brigham S. Anderson, Andrew W. Moore, David Cohn
WWW
2008
ACM
16 years 7 months ago
Ranking refinement and its application to information retrieval
We consider the problem of ranking refinement, i.e., to improve the accuracy of an existing ranking function with a small set of labeled instances. We are, particularly, intereste...
Rong Jin, Hamed Valizadegan, Hang Li
SSDBM
2010
IEEE
188views Database» more  SSDBM 2010»
15 years 11 months ago
Similarity Estimation Using Bayes Ensembles
Similarity search and data mining often rely on distance or similarity functions in order to provide meaningful results and semantically meaningful patterns. However, standard dist...
Tobias Emrich, Franz Graf, Hans-Peter Kriegel, Mat...
CVPR
2007
IEEE
16 years 8 months ago
Utilizing Variational Optimization to Learn Markov Random Fields
Markov Random Field, or MRF, models are a powerful tool for modeling images. While much progress has been made in algorithms for inference in MRFs, learning the parameters of an M...
Marshall F. Tappen
ECCV
2008
Springer
16 years 8 months ago
Discriminative Learning for Deformable Shape Segmentation: A Comparative Study
Abstract. We present a comparative study on how to use discriminative learning methods such as classification, regression, and ranking to address deformable shape segmentation. Tra...
Jingdan Zhang, Shaohua Kevin Zhou, Dorin Comaniciu...