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» Missing Data Estimation Using Polynomial Kernels
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IPSN
2004
Springer
15 years 5 months ago
Estimation from lossy sensor data: jump linear modeling and Kalman filtering
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
BMVC
2001
15 years 2 months ago
A Buyer's Guide to Euclidean Elliptical Cylindrical and Conical Surface Fitting
The ability to construct CAD or other object models from edge and range data has a fundamental meaning in building a recognition and positioning system. While the problem of model...
Petko Faber, Robert B. Fisher
PR
2010
156views more  PR 2010»
14 years 11 months ago
Semi-supervised clustering with metric learning: An adaptive kernel method
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
Xuesong Yin, Songcan Chen, Enliang Hu, Daoqiang Zh...
ICMLA
2009
14 years 10 months ago
ECON: A Kernel Basis Pursuit Algorithm with Automatic Feature Parameter Tuning, and its Application to Photometric Solids Approx
This paper introduces a new algorithm, namely the EquiCorrelation Network (ECON), to perform supervised classification, and regression. ECON is a kernelized LARS-like algorithm, b...
Manuel Loth, Philippe Preux, Samuel Delepoulle, Ch...
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ICIP
2005
IEEE
16 years 2 months ago
A spatially adaptive Poissonian image deblurring
A spatially adaptive image deblurring algorithm is presented for Poisson observations. It adapts to the unknown image smoothness by using local polynomial approximation (LPA) kern...
Alessandro Foi, Sakari Alenius, Mejdi Trimeche, Vl...