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» Laplacian Spectrum Learning
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ICML
2009
IEEE
15 years 10 months ago
The graphlet spectrum
Risi Imre Kondor, Nino Shervashidze, Karsten M. Bo...
NIPS
2008
14 years 11 months ago
Spectral Hashing
Semantic hashing[1] seeks compact binary codes of data-points so that the Hamming distance between codewords correlates with semantic similarity. In this paper, we show that the p...
Yair Weiss, Antonio Torralba, Robert Fergus
102
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ML
2010
ACM
193views Machine Learning» more  ML 2010»
14 years 4 months ago
On the eigenvectors of p-Laplacian
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...
Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping N...
89
Voted
COLT
2005
Springer
15 years 3 months ago
From Graphs to Manifolds - Weak and Strong Pointwise Consistency of Graph Laplacians
In the machine learning community it is generally believed that graph Laplacians corresponding to a finite sample of data points converge to a continuous Laplace operator if the s...
Matthias Hein, Jean-Yves Audibert, Ulrike von Luxb...
111
Voted
NIPS
2004
14 years 11 months ago
Modeling Nonlinear Dependencies in Natural Images using Mixture of Laplacian Distribution
Capturing dependencies in images in an unsupervised manner is important for many image processing applications. We propose a new method for capturing nonlinear dependencies in ima...
Hyun-Jin Park, Te-Won Lee