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» Computing LTS Regression for Large Data Sets
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CVPR
2008
IEEE
16 years 6 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 4 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 ...
147
Voted
NIPS
1997
15 years 5 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 5 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 9 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