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ICASSP
2009
IEEE
15 years 4 months ago
Ensembles of landmark multidimensional scalings
Landmark multidimensional scaling (LMDS) uses a subset of data (landmark points) to solve classical MDS, where the scalability is increased but the approximation is noise-sensitiv...
Seunghak Lee, Seungjin Choi
154
Voted
CORR
2010
Springer
152views Education» more  CORR 2010»
15 years 6 months ago
Microlocal Analysis of the Geometric Separation Problem
Image data are often composed of two or more geometrically distinct constituents; in galaxy catalogs, for instance, one sees a mixture of pointlike structures (galaxy supercluster...
David L. Donoho, Gitta Kutyniok
CORR
2010
Springer
121views Education» more  CORR 2010»
15 years 1 months ago
Deep Self-Taught Learning for Handwritten Character Recognition
Recent theoretical and empirical work in statistical machine learning has demonstrated the importance of learning algorithms for deep architectures, i.e., function classes obtaine...
Frédéric Bastien, Yoshua Bengio, Arn...
CVPR
2008
IEEE
16 years 8 months ago
Sequential particle swarm optimization for visual tracking
Visual tracking usually involves an optimization process for estimating the motion of an object from measured images in a video sequence. In this paper, a new evolutionary approac...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...
CGF
1999
98views more  CGF 1999»
15 years 6 months ago
Multiresolution Curve and Surface Representation: Reversing Subdivision Rules by Least-Squares Data Fitting
This work explores how three techniques for defining and representing curves and surfaces can be related efficiently. The techniques are subdivision, least-squares data fitting, a...
Faramarz F. Samavati, Richard M. Bartels
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