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TIP
2010
182views more  TIP 2010»
15 years 1 months ago
Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction
We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the ...
Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changsh...
ALT
2004
Springer
16 years 3 months ago
On Kernels, Margins, and Low-Dimensional Mappings
Kernel functions are typically viewed as providing an implicit mapping of points into a high-dimensional space, with the ability to gain much of the power of that space without inc...
Maria-Florina Balcan, Avrim Blum, Santosh Vempala
BMCV
2000
Springer
15 years 11 months ago
The Spectral Independent Components of Natural Scenes
Abstract. We apply independent component analysis (ICA) for learning an efficient color image representation of natural scenes. In the spectra of single pixels, the algorithm was a...
Te-Won Lee, Thomas Wachtler, Terrence J. Sejnowski
TKDE
2008
171views more  TKDE 2008»
15 years 6 months ago
Efficient Similarity Search in Nonmetric Spaces with Local Constant Embedding
Similarity-based search has been a key factor for many applications such as multimedia retrieval, data mining, Web search and retrieval, and so on. There are two important issues r...
Lei Chen 0002, Xiang Lian
STACS
2010
Springer
16 years 1 months ago
Two-phase Algorithms for the Parametric Shortest Path Problem
Abstract. A parametric weighted graph is a graph whose edges are labeled with continuous real functions of a single common variable. For any instantiation of the variable, one obta...
Sourav Chakraborty, Eldar Fischer, Oded Lachish, R...