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» Computing LTS Regression for Large Data Sets
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CVPR
2008
IEEE
16 years 8 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
SIGMOD
2002
ACM
127views Database» more  SIGMOD 2002»
16 years 6 months ago
Approximate XML joins
XML is widely recognized as the data interchange standard for tomorrow, because of its ability to represent data from a wide variety of sources. Hence, XML is likely to be the for...
Sudipto Guha, H. V. Jagadish, Nick Koudas, Divesh ...
NIPS
1997
15 years 7 months ago
EM Algorithms for PCA and SPCA
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
Sam T. Roweis
DAC
1999
ACM
16 years 7 months ago
Behavioral Synthesis Techniques for Intellectual Property Protection
? The economic viability of the reusable core-based design paradigm depends on the development of techniques for intellectual property protection. We introduce the first dynamic wa...
Inki Hong, Miodrag Potkonjak
ESORICS
2005
Springer
15 years 12 months ago
Privacy Preserving Clustering
The freedom and transparency of information flow on the Internet has heightened concerns of privacy. Given a set of data items, clustering algorithms group similar items together...
Somesh Jha, Louis Kruger, Patrick McDaniel