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» Sparse PCA: Extracting Multi-scale Structure from Data
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126
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NC
2007
129views Neural Networks» more  NC 2007»
15 years 19 days ago
Sorting of neural spikes: When wavelet based methods outperform principal component analysis
Sorting of the extracellularly recorded spikes is a basic prerequisite for analysis of the cooperative neural behavior and neural code. Fundamentally the sorting performance is deï...
Alexey N. Pavlov, Valeri A. Makarov, Ioulia Makaro...
127
Voted
AAAI
2008
15 years 3 months ago
Sparse Projections over Graph
Recent study has shown that canonical algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) can be obtained from graph based dimensionality ...
Deng Cai, Xiaofei He, Jiawei Han
132
Voted
PAMI
1998
197views more  PAMI 1998»
15 years 24 days ago
Inference of Integrated Surface, Curve, and Junction Descriptions From Sparse 3D Data
—We are interested in descriptions of 3D data sets, as obtained from stereo or a 3D digitizer. We therefore consider as input a sparse set of points, possibly associated with cer...
Chi-Keung Tang, Gérard G. Medioni
123
Voted
ICCV
1998
IEEE
15 years 5 months ago
Integrated Surface, Curve and Junction Inference from Sparse 3-D Data Sets
We areinterestedin descriptionsof 3-D data sets,as obtained from stereoor a 3-D digitizer. We thereforeconsideras inputa sparsesetof points, possibly associated with certain orien...
Chi-Keung Tang, Gérard G. Medioni
107
Voted
RECOMB
2001
Springer
15 years 5 months ago
Extracting structural information using time-frequency analysis of protein NMR data
High-throughput, data-directed computational protocols for Structural Genomics (or Proteomics) are required in order to evaluate the protein products of genes for structure and fu...
Christopher James Langmead, Bruce Randall Donald