In the machine learning field, feature selection is used to discard the redundant information and improve the learning accuracy. In this paper, the redundant information is reused in the learning of partial least squares method within the frame of multitask learning. This newly proposed method is used to solve the multivariate calibration problem, a classic problem in the analytical chemistry f...

The main contributions of this paper can be summarized as follows. First, we compare the Partial Least Squares (PLS) and the Principal Component Analysis (PCA), under fairly general conditions. (In particular, the existence of a true linear regression is not assumed.) We prove that PLS and PCA are equivalent, to within a rst-order approximation, hence providing a theoretical explanation for emp...

In this work we find out how PLS algorithms, properly adjusted, can work as optimal scaling algorithms. This new feature of PLS, which had until now been totally unexplored, allowed us to devise a new suite of PLS methods: the Non-Metric PLS (NM-PLS) methods. Mots-clès: Analyse des données data mining, Problèmes inverses et sparsité

The purpose of the present article is to take stock of a recent exchange in Organizational Research Methods between critics and proponents of partial least squares path modeling (PLS-PM). The two target articles were centered around six principal issues, namely whether PLS-PM: (a) can be truly characterized as a technique for structural equation modeling (SEM), (b) is able to correct for measur...

I-vectors are a concise representation of speaker characteristics. Recent advances in speaker recognition have utilized their ability to capture speaker and channel variability to develop efficient recognition engines. Inter-speaker relationships in the ivector space are non-linear. Accomplishing effective speaker recognition requires a good modeling of these non-linearities and can be cast as ...

Face identification is an important research topic due to areas such as its application to surveillance, forensics and human-computer interaction. In the past few years, a myriad of methods for face identification has been proposed in the literature, with just a few among them focusing on scalability. In this work, we propose a simple but efficient approach for scalable face identification base...

We prove the statistical consistency of kernel Partial Least Squares Regression applied to a bounded regression learning problem on a reproducing kernel Hilbert space. Partial Least Squares stands out of well-known classical approaches as e.g. Ridge Regression or Principal Components Regression, as it is not defined as the solution of a global cost minimization procedure over a fixed model nor ...

Partial least squares (PLS) is a widely used method for prediction in applied statistics, especially in chemometrics applications. However, PLS is not invariant or equivariant under scale transformations of the predictors, which tends to limit its scope to regressions in which the predictors are measured in the same or similar units. Cook et al. (2013) built a connect between nascent envelope m...

Social Media has been gaining popularity worldwide over the last years at an increasingly growing rate. Motivated by this fact, firms are piloting different approaches of promoting their products and services to consumers in order to capitalize on the prominence of such websites. However, there is much debate in the academic and business community about the potential of social media as a platfo...

In social networking sites (SNSs), the user has a dual role as one produces content for both oneself and for the other users, and consumes the content produced by other users. Thus, we argue the SNS users can be characterized as prosumers. Drawing on the Uses & Gratifications approach, we further argue that voyeurism and exhibitionism are important gratifications from prosuming SNSs. We thus ex...