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SMI
2010
IEEE
165views Image Analysis» more  SMI 2010»
14 years 9 months ago
Designing a Topological Modeler Kernel: A Rule-Based Approach
In this article, we present a rule-based language dedicated to topological operations, based on graph transformations. Generalized maps are described as a particular class of graph...
Thomas Bellet, Mathieu Poudret, Agnès Arnou...
CORR
2008
Springer
100views Education» more  CORR 2008»
14 years 11 months ago
Learning Isometric Separation Maps
Maximum Variance Unfolding (MVU) and its variants have been very successful in embedding data-manifolds in lower dimensionality spaces, often revealing the true intrinsic dimensio...
Nikolaos Vasiloglou, Alexander G. Gray, David V. A...
ICASSP
2008
IEEE
15 years 6 months ago
Robust kernel density estimation
In this paper, we propose a method for robust kernel density estimation. We interpret a KDE with Gaussian kernel as the inner product between a mapped test point and the centroid ...
JooSeuk Kim, Clayton Scott
ACCV
2009
Springer
15 years 3 months ago
Accurate and Efficient Cost Aggregation Strategy for Stereo Correspondence Based on Approximated Joint Bilateral Filtering
Recent local state-of-the-art stereo algorithms based on variable cost aggregation strategies allow for inferring disparity maps comparable to those yielded by algorithms based on ...
Stefano Mattoccia, Simone Giardino, Andrea Gambini
ICML
2004
IEEE
15 years 5 months ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul