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TNN
2008
128views more  TNN 2008»
13 years 8 months ago
Nonnegative Matrix Factorization in Polynomial Feature Space
Abstract--Plenty of methods have been proposed in order to discover latent variables (features) in data sets. Such approaches include the principal component analysis (PCA), indepe...
Ioan Buciu, Nikos Nikolaidis, Ioannis Pitas
ICDCS
2012
IEEE
11 years 10 months ago
Scalable Name Lookup in NDN Using Effective Name Component Encoding
—Name-based route lookup is a key function for Named Data Networking (NDN). The NDN names are hierarchical and have variable and unbounded lengths, which are much longer than IPv...
Yi Wang, Keqiang He, Huichen Dai, Wei Meng, Junche...
TNN
2008
182views more  TNN 2008»
13 years 8 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
CIKM
2009
Springer
14 years 2 months ago
Completing wikipedia's hyperlink structure through dimensionality reduction
Wikipedia is the largest monolithic repository of human knowledge. In addition to its sheer size, it represents a new encyclopedic paradigm by interconnecting articles through hyp...
Robert West, Doina Precup, Joelle Pineau

Publication
170views
13 years 7 months ago
Covariance Regularization for Supervised Learning in High Dimensions
This paper studies the effect of covariance regularization for classific ation of high-dimensional data. This is done by fitting a mixture of Gaussians with a regularized covaria...
Daniel L. Elliott, Charles W. Anderson, Michael Ki...