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JMLR
2008
79views more  JMLR 2008»
14 years 9 months ago
Manifold Learning: The Price of Normalization
We analyze the performance of a class of manifold-learning algorithms that find their output by minimizing a quadratic form under some normalization constraints. This class consis...
Yair Goldberg, Alon Zakai, Dan Kushnir, Yaacov Rit...
NIPS
2000
14 years 11 months ago
A Silicon Primitive for Competitive Learning
Competitive learning is a technique for training classification and clustering networks. We have designed and fabricated an 11transistor primitive, that we term an automaximizing ...
David Hsu, Miguel Figueroa, Chris Diorio
NIPS
2007
14 years 11 months ago
Privacy-Preserving Belief Propagation and Sampling
We provide provably privacy-preserving versions of belief propagation, Gibbs sampling, and other local algorithms — distributed multiparty protocols in which each party or verte...
Michael Kearns, Jinsong Tan, Jennifer Wortman
MLDM
2007
Springer
15 years 3 months ago
Outlier Detection with Kernel Density Functions
Abstract. Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel unsupervised algorithm for outlier detec...
Longin Jan Latecki, Aleksandar Lazarevic, Dragolju...
ACCV
2007
Springer
15 years 4 months ago
Hierarchical Learning of Dominant Constellations for Object Class Recognition
Abstract. The importance of spatial configuration information for object class recognition is widely recognized. Single isolated local appearance codes are often ambiguous. On the...
Nathan Mekuz, John K. Tsotsos