Outliers are identified by tuning a regularization parameter, which amounts to controlling the sparsity of an outlier vector along the entire ro- bustification ...
The goal of PM is to learn the utility function of an individual or a group of individuals from expressed preference data (buying patterns, surveys, ratings), ...
Outliers are identified by tuning a regularization parameter, which amounts to controlling the sparsity of an outlier vector along the entire ro-bustification ...
Robust conjoint analysis by controlling outlier sparsity. Mateos, Gonzalo, Giannakis, Georgios B. Details · Contributors · Fields of science · Bibliography ...
Sparsity control for robust principal component analysis - IEEE Xplore
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Outliers are identified by tuning a regularization parameter, which amounts to controlling the sparsity of the outlier matrix along the whole robustification ...
Missing: conjoint | Show results with:conjoint
Mateos and G. B. Giannakis, ``Robust Conjoint Analysis by Controlling Outlier Sparsity,'' Proc. of European Signal Processing Conference, Barcelona, Spain ...
Links between sparsity and robustness against outliers exploiting connections with the -norm were drawn in the linear regression context in [12], [13], and more.
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Outliers are handled through auxiliary unknown variables that are jointly estimated along with the state based on the least-squares criterion regularized with ...
Missing: conjoint | Show results with:conjoint
A new statistical model for choice-based conjoint analysis is proposed. The model uses auxiliary variables to account for outliers.
Jul 1, 2021 · Abstract. We propose a data-analytic method for detecting cellwise outliers. Given a robust covariance matrix, outlying cells (entries) in a ...