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» Clustering Large Datasets in Arbitrary Metric Spaces
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ICIP
2003
IEEE
14 years 9 months ago
Kernel indexing for relevance feedback image retrieval
Relevance feedback is an attractive approach to developing flexible metrics for content-based retrieval in image and video databases. Large image databases require an index struct...
Jing Peng, Douglas R. Heisterkamp
CIKM
2006
Springer
13 years 9 months ago
Efficiently clustering transactional data with weighted coverage density
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Hua Yan, Keke Chen, Ling Liu
CSB
2005
IEEE
205views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Fractal Clustering for Microarray Data Analysis
DNA microarray experiments generate a substantial amount of information about global gene expression. Gene expression profiles can be represented as points in multi-dimensional sp...
Lu-Yong Wang, Ammaiappan Balasubramanian, Amit Cha...
ML
2010
ACM
124views Machine Learning» more  ML 2010»
13 years 5 months ago
Large scale image annotation: learning to rank with joint word-image embeddings
Image annotation datasets are becoming larger and larger, with tens of millions of images and tens of thousands of possible annotations. We propose a strongly performing method tha...
Jason Weston, Samy Bengio, Nicolas Usunier
ICML
2005
IEEE
14 years 8 months ago
Large margin non-linear embedding
It is common in classification methods to first place data in a vector space and then learn decision boundaries. We propose reversing that process: for fixed decision boundaries, ...
Alexander Zien, Joaquin Quiñonero Candela