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» Watermarking relational data: framework, algorithms and anal...
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JCB
2002
93views more  JCB 2002»
14 years 11 months ago
Unfolding of Microarray Data
The use of DNA microarrays for the analysis of complex biological samples is becoming a mainstream part of biomedical research. One of the most commonly used methods compares the ...
Andrew B. Goryachev, Pascale F. Macgregor, Aled M....
ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
15 years 5 months ago
Worst-Case and Smoothed Analysis of k-Means Clustering with Bregman Divergences
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Bodo Manthey, Heiko Röglin
SIGMOD
2003
ACM
150views Database» more  SIGMOD 2003»
15 years 11 months ago
Capturing both Types and Constraints in Data Integration
We propose a framework for integrating data from multiple relational sources into an XML document that both conforms to a given DTD and satisfies predefined XML constraints. The f...
Michael Benedikt, Chee Yong Chan, Wenfei Fan, Juli...
PAMI
2012
13 years 1 months ago
Image Signature: Highlighting Sparse Salient Regions
—We introduce a simple image descriptor referred to as the image signature. We show, within the theoretical framework of sparse signal mixing, that this quantity spatially approx...
Xiaodi Hou, Jonathan Harel, Christof Koch
ICML
2005
IEEE
16 years 1 days ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore