Robust Linear Clustering with Least Squares Criterion and Its Application to Collaborative Filtering
نویسندگان
چکیده
منابع مشابه
Supplement to “ Robust Linear Least Squares Regression ”
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau...
متن کاملTo “ Robust Linear Least Squares Regression ”
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau...
متن کاملRobust linear least squares regression
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau...
متن کاملRobust Least-Squares Filtering With a Relative Entropy Constraint
We formulate a robust Wiener filtering problem for wide-sense stationary (WSS) Gaussian processes in the presence of modelling errors. It requires solving a minimax problem that consists of finding the best filter for the least-favorable statistical model within a neighborhood of the nominal model. The neighborhood is formed by models whose relative entropy with respect to the nominal model is ...
متن کاملApplication of Recursive Least Squares to Efficient Blunder Detection in Linear Models
In many geodetic applications a large number of observations are being measured to estimate the unknown parameters. The unbiasedness property of the estimated parameters is only ensured if there is no bias (e.g. systematic effect) or falsifying observations, which are also known as outliers. One of the most important steps towards obtaining a coherent analysis for the parameter estimation is th...
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ژورنال
عنوان ژورنال: Transactions of the Institute of Systems, Control and Information Engineers
سال: 2003
ISSN: 1342-5668,2185-811X
DOI: 10.5687/iscie.16.597