—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 ...
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...
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, ...
Abstract. Two new techniques based on nonparametric estimation of probability densities are introduced which improve on the performance of equivalent robust methods currently emplo...
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...