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PR
2006
147views more  PR 2006»
14 years 9 months ago
Robust locally linear embedding
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
Hong Chang, Dit-Yan Yeung
COMPLEXITY
2010
124views more  COMPLEXITY 2010»
14 years 7 months ago
Spatially embedded dynamics and complexity
To gain a deeper understanding of the impact of spatial embedding on the dynamics of complex systems we employ a measure of interaction complexity developed within neuroscience us...
Christopher L. Buckley, Seth Bullock, Lionel Barne...
ICML
2009
IEEE
15 years 10 months ago
Partial order embedding with multiple kernels
We consider the problem of embedding arbitrary objects (e.g., images, audio, documents) into Euclidean space subject to a partial order over pairwise distances. Partial order cons...
Brian McFee, Gert R. G. Lanckriet
ICPR
2008
IEEE
15 years 4 months ago
Semi-supervised learning by locally linear embedding in kernel space
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
Rujie Liu, Yuehong Wang, Takayuki Baba, Daiki Masu...
NIPS
2004
14 years 11 months ago
Multiple Relational Embedding
We describe a way of using multiple different types of similarity relationship to learn a low-dimensional embedding of a dataset. Our method chooses different, possibly overlappin...
Roland Memisevic, Geoffrey E. Hinton