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ISCAS
2006
IEEE
107views Hardware» more  ISCAS 2006»
15 years 5 months ago
Assessment of probability density estimation methods: Parzen window and finite Gaussian mixtures
—Probability Density Function (PDF) estimation is a very critical task in many applications of data analysis. For example in the Bayesian framework decisions are taken according ...
Cédric Archambeau, M. Valle, A. Assenza, Mi...
ML
2002
ACM
111views Machine Learning» more  ML 2002»
14 years 11 months ago
Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data
Binningandtruncationofdataarecommonindataanalysisandmachinelearning.Thispaperaddresses the problem of fitting mixture densities to multivariate binned and truncated data. The EM ap...
Igor V. Cadez, Padhraic Smyth, Geoffrey J. McLachl...
DATE
2008
IEEE
226views Hardware» more  DATE 2008»
15 years 6 months ago
A General Method to Evaluate RF BIST Techniques Based on Non-parametric Density Estimation
Abstract— We present a general method to evaluate RF BuiltIn Self-Test (BIST) techniques during the design stage. In particular, the adaptive kernel estimator is used to construc...
Haralampos-G. D. Stratigopoulos, Jeanne Tongbong, ...
ECCV
2002
Springer
16 years 1 months ago
Robust Computer Vision through Kernel Density Estimation
Abstract. Two new techniques based on nonparametric estimation of probability densities are introduced which improve on the performance of equivalent robust methods currently emplo...
Haifeng Chen, Peter Meer
CSL
1998
Springer
14 years 11 months ago
Model parameter estimation for mixture density polynomial segment models
In this paper, we propose parameter estimation techniques for mixture density polynomial segment models (MDPSMs) where their trajectories are specified with an arbitrary regressi...
Toshiaki Fukada, Kuldip K. Paliwal, Yoshinori Sagi...