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» Missing Data Estimation Using Polynomial Kernels
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ICAPR
2005
Springer
13 years 10 months ago
Missing Data Estimation Using Polynomial Kernels
Abstract. In this paper, we deal with the problem of partially observed objects. These objects are defined by a set of points and their shape variations are represented by a statis...
Maxime Berar, Michel Desvignes, Gérard Bail...
ADCM
2008
187views more  ADCM 2008»
13 years 4 months ago
Approximation on the sphere using radial basis functions plus polynomials
In this paper we analyse a hybrid approximation of functions on the sphere S2 R3 by radial basis functions combined with polynomials, with the radial basis functions assumed to be...
Ian H. Sloan, Alvise Sommariva
ICDM
2007
IEEE
145views Data Mining» more  ICDM 2007»
13 years 11 months ago
Using Data Mining to Estimate Missing Sensor Data
Estimating missing sensor values is an inherent problem in sensor network applications; however, existing data estimation approaches do not apply well to the context of datastream...
Le Gruenwald, Hamed Chok, Mazen Aboukhamis
KDD
2006
ACM
181views Data Mining» more  KDD 2006»
14 years 5 months ago
Cryptographically private support vector machines
We study the problem of private classification using kernel methods. More specifically, we propose private protocols implementing the Kernel Adatron and Kernel Perceptron learning ...
Helger Lipmaa, Sven Laur, Taneli Mielikäinen
AINA
2008
IEEE
13 years 11 months ago
Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
Connie Phong, Raul Singh