This paper addresses the problems of learning from labelled data contextual discounting and contextual reinforcement, two correction schemes recently introduced in belief function theory. It shows that given a particular error criterion based on the plausibility function, for each of these two contextual correction schemes, there exists an optimal set of contexts that ensures the minimization o...

A recent study on the condition numbers of mixed least squares-total squares (MTLS) problem is due to Zheng and Yang (Numer Linear Algebra Appl. 2019;26(4):e2239). However, associated expressions are not compact Kronecker-product operations make computation costly. In this paper, we first present new alternative closed formula for order perturbation estimate MTLS solution. Then reveal relations...

selecting a IUDFWLRQDO H[SRQHQWLDO )(;3 model for a Gaussian long-memory time series. A regression approach is used to obtain the least squares estimator of d of the memory parameter, and mean squared error is minimized. The paper overlooks the fact that in the case of regression models, there is a relationship between $NDLNH¶V LQIRUPDWLRQ FULWHULRQ $,& and 0DOORZV¶ / & , which can also be used...

The quality of short-term electricity load forecasting is crucial to the operations and trading activities of market participants in an electricity market. In this paper, a multiple equation time series model for intra-day and day-ahead load forecasting is built. The model uses lagged load and temperature as the primary explanatory variables but makes effective use of diurnal characteristics an...

Recent studies have demonstrated that correntropy is an efficient tool for analyzing higher-order statistical moments in nonGaussian noise environments. Although correntropy has been used with complex data, no theoretical study was pursued to elucidate its properties, nor how to best use it for optimization . This paper presents a probabilistic interpretation for correntropy using complex-value...

We present a methodology for adaptive ltering and system identi cation under the cyclostationary regime. Our technique is based on a deterministic periodic least-squares criterion, and gives rise to adaptive periodic recursive-least-squares (P-RLS) algorithms. Furthermore, we show that every adaptive RLS algorithm has a P-RLS counterpart, which has exactly the same architecture and the same per...

This paper introduces and solves a weighted game-type cost criterion for estimation and control purposes that allows for a general class of uncertainties in the model or data. Both structured and unstructured uncertainties are allowed, including some special cases that have been used in the literature. The optimal solution is shown to satisfy an orthogonality condition similar to least-squares ...