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Higher-Order Partial Least Squares (HOPLS) : a generalized multi-linear regression method
(IEEE Computer Society, 2013-07)
A new generalized multilinear regression model, termed the Higher-Order Partial Least Squares (HOPLS), is introduced with the aim to predict a tensor (multiway array) Y from a tensor X through projecting the data onto the ...
Constrained smoothing B-splines for the term structure of interest rates
(Elsevier Science BvAmsterdamHolanda, 2010)
Risk-constrained forward trading optimization through stochastic approximate dynamic programming
(IntechOpen, 2014)
Since the mid-twentieth century, Dynamic Programming (DP) has proved to be a flexible and powerful approach to address optimal decisions problems. Nevertheless, a decisive drawback of the conventional DP is the need for ...
Finding archetypal patterns for binary questionnaires
One of the main challenges researchers face is to identify the most relevant features in a prediction model. As a consequence, many regularized methods seeking sparsity have flourished. Although sparse, their solutions may ...
High finite-sample efficiency and robustness based on distance-constrained maximum likelihood
(Elsevier Science, 2015-03)
Good robust estimators can be tuned to combine a high breakdown point and a specified asymptotic efficiency at a central model. This happens in regression with MM- and -estimators among others. However, the finite-sample ...
Investor protection and constraints relief
(2016-12-22)
Under financial constraints, firms are kept from following first-best policies. It is in the best interests of the regulators to diminish this inefficiencies as firms play such a important roles in the economy as generating ...