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» A theory of learning with similarity functions
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CVPR
2010
IEEE
15 years 7 months ago
SPEC Hashing: Similarity Preserving algorithm for Entropy-based Coding
Searching approximate nearest neighbors in large scale high dimensional data set has been a challenging problem. This paper presents a novel and fast algorithm for learning binary...
Ruei-Sung Lin, David Ross, Jay Yagnik
BMCBI
2004
140views more  BMCBI 2004»
14 years 11 months ago
What can we learn from noncoding regions of similarity between genomes?
Background: In addition to known protein-coding genes, large amounts of apparently non-coding sequence are conserved between the human and mouse genomes. It seems reasonable to as...
Thomas A. Down, Tim J. P. Hubbard
KDD
2012
ACM
188views Data Mining» more  KDD 2012»
13 years 2 months ago
A probabilistic model for multimodal hash function learning
In recent years, both hashing-based similarity search and multimodal similarity search have aroused much research interest in the data mining and other communities. While hashing-...
Yi Zhen, Dit-Yan Yeung
CVPR
2003
IEEE
16 years 1 months ago
Learning Affinity Functions for Image Segmentation: Combining Patch-based and Gradient-based Approaches
This paper studies the problem of combining region and boundary cues for natural image segmentation. We employ a large database of manually segmented images in order to learn an o...
Charless Fowlkes, David R. Martin, Jitendra Malik
SSDBM
2010
IEEE
188views Database» more  SSDBM 2010»
15 years 4 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...