Feature learning forms the cornerstone for tackling challenging learning problems in domains such as speech, computer vision and natural language processing. In this paper, we consider a novel class of matrix and tensor-valued features, which can be pre-trained using unlabeled samples. We present efficient algorithms for extracting discriminative information, given these pre-trained features an...

This work introduces a new density estimation method based integrating an estimated score function. The score function is itself estimated by the minimization of a L 2 square distance with an added roughness penalty, resulting in a spline function. A computational algorithm is developed for this purpose. The asymptotic behavior of the estimators is studied under the light of a kernel representa...

OBJECTIVE — Success after islet transplantation can be defined in terms of insulin independence, C-peptide secretion, or glycemic control. These measures are interdependent and all need to be considered in evaluating -cell function after islet transplantation. For the current study, a composite -score was developed that provides an integrated measure of -cell function success after islet transp...

background: chronic obstructive pulmonary disease (copd) is a major public health problem worldwide. smoking is the number one cause of copd; however, genetic, environmental and dietary factors contribute to the etiology of this disease. in this study, we assessed the association between three diet quality indices -the healthy eating index-2005 (hei-2005), the healthy eating index-2010 (hei-201...

Feature learning forms the cornerstone for tackling challenging learning problems in domains such as speech, computer vision and natural language processing. In this paper, we consider a novel class of matrix and tensor-valued features, which can be pre-trained using unlabeled samples. We present efficient algorithms for extracting discriminative information, given these pre-trained features an...

Feature learning forms the cornerstone for tackling challenging learning problems in domains such as speech, computer vision and natural language processing. In this paper, we build upon a novel framework called FEAST(Feature ExtrAction using Score function Tensors) which incorporates generative models for discriminative learning. FEAST considers a novel class of matrix and tensor-valued featur...

The objective of this paper is to develop matrix games with pay-offs of triangular hesitant fuzzy elements (THFEs). To solve such games, a new methodology has been derived based on the notion of weighted average operator and score function of THFEs. Firstly, we formulate two non-linear programming problems with THFEs. Then applying the score function of THFEs, we transform these two problems in...

Introduction: Breastfeeding is the ideal source of nutrition for infants. However, there is controversy regarding the effect of breastfeeding on mothers’ sexual function. Therefore, this study aimed to assess the relationship between postpartum sexual function and infant feeding method in women referring to Mashhad healthcare centers. Methods: This descriptive, analytical study was performed o...