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» Local Dimensionality Reduction
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80
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NIPS
2007
15 years 1 months ago
Colored Maximum Variance Unfolding
Maximum variance unfolding (MVU) is an effective heuristic for dimensionality reduction. It produces a low-dimensional representation of the data by maximizing the variance of the...
Le Song, Alex J. Smola, Karsten M. Borgwardt, Arth...
104
Voted
SSIAI
2002
IEEE
15 years 5 months ago
Two Dimensional Projective Point Matching
Point matching is the task of finding a set of correspondences between two sets of points under some geometric transformation. A local search algorithm for point matching is pres...
Jason Denton, J. Ross Beveridge
110
Voted
CVPR
2007
IEEE
16 years 2 months ago
Approximate Nearest Subspace Search with Applications to Pattern Recognition
Linear and affine subspaces are commonly used to describe appearance of objects under different lighting, viewpoint, articulation, and identity. A natural problem arising from the...
Ronen Basri, Tal Hassner, Lihi Zelnik-Manor
ICML
2007
IEEE
16 years 1 months ago
Sparse eigen methods by D.C. programming
Eigenvalue problems are rampant in machine learning and statistics and appear in the context of classification, dimensionality reduction, etc. In this paper, we consider a cardina...
Bharath K. Sriperumbudur, David A. Torres, Gert R....
96
Voted
APBC
2004
117views Bioinformatics» more  APBC 2004»
15 years 1 months ago
Detecting Local Symmetry Axis in 3-dimensional Virus Structures
This paper presents an efficient computational method to identify a local symmetry axis in 3-dimensional viral structures obtained using electron cryomicroscopy. Local symmetry is...
Jing He, Desh Ranjan, Wen Jiang, Wah Chiu, Michael...