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» On the Hamkins approximation property
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JMLR
2010
103views more  JMLR 2010»
15 years 1 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Tzu-Kuo Huang, Le Song, Jeff Schneider
JSCIC
2010
101views more  JSCIC 2010»
15 years 1 months ago
Boundary-Conforming Discontinuous Galerkin Methods via Extensions from Subdomains
A new way of devising numerical methods is introduced whose distinctive feature is the computation of a finite element approximation only in a polyhedral subdomain D of the origina...
Bernardo Cockburn, Deepa Gupta, Fernando Reitich
TSP
2011
96views more  TSP 2011»
15 years 25 days ago
A Signal Processing Approach to Fourier Analysis of Ranking Data: The Importance of Phase
—Ranking data is a type of data obtained in some elections, in customer surveys, as well as from web search results. Such data may be considered as a type of signal defined on t...
Ramakrishna Kakarala
ECCV
2002
Springer
16 years 8 months ago
Regularized Shock Filters and Complex Diffusion
We address the issue of regularizing Osher and Rudin's shock filter, used for image deblurring, in order to allow processes that are more robust against noise. Previous soluti...
Guy Gilboa, Nir A. Sochen, Yehoshua Y. Zeevi
ICIP
2005
IEEE
16 years 8 months ago
Sampling schemes for 2-D signals with finite rate of innovation using kernels that reproduce polynomials
In this paper, we propose new sampling schemes for classes of 2-D signals with finite rate of innovation (FRI). In particular, we consider sets of 2-D Diracs and bilevel polygons....
Pancham Shukla, Pier Luigi Dragotti