Sparse modeling using orthogonal forward regression with PRESS statistic and regularization

The paper introduces an efficient construction algorithm for obtaining sparse linear-in-the-weights regression models based on an approach of directly optimizing model generalization capability. This is achieved by utilizing the delete-1 cross validation concept and the associated leave-one-out test error also known as the predicted residual sums of squares (PRESS) statistic, without resorting to any other validation data set for model evaluation in the model construction process. Computational efficiency is ensured using an orthogonal forward regression, but the algorithm incrementally minimizes the PRESS statistic instead of the usual sum of the squared training errors. A local regularization method can naturally be incorporated into the model selection procedure to further enforce model sparsity. The proposed algorithm is fully automatic, and the user is not required to specify any criterion to terminate the model construction procedure. Comparisons with some of the existing state-of-art modeling methods are given, and several examples are included to demonstrate the ability of the proposed algorithm to effectively construct sparse models that generalize well.

A robust nonlinear identification algorithm using PRESS statistic and forward regression

This letter introduces a new robust nonlinear identification algorithm using the Predicted REsidual Sums of Squares (PRESS) statistic and for-ward regression. The major contribution is to compute the PRESS statistic within a framework of a forward orthogonalization process and hence construct a model with a good generalization property. Based on the properties of the PRESS statistic the proposed algorithm can achieve a fully automated procedure without resort to any other validation data set for iterative model evaluation.

Automatic nonlinear predictive model-construction algorithm using forward regression and the PRESS statistic

An automatic nonlinear predictive model-construction algorithm is introduced based on forward regression and the predicted-residual-sums-of-squares (PRESS) statistic. The proposed algorithm is based on the fundamental concept of evaluating a model's generalisation capability through crossvalidation. This is achieved by using the PRESS statistic as a cost function to optimise model structure. In particular, the proposed algorithm is developed with the aim of achieving computational efficiency, such that the computational effort, which would usually be extensive in the computation of the PRESS statistic, is reduced or minimised. The computation of PRESS is simplified by avoiding a matrix inversion through the use of the orthogonalisation procedure inherent in forward regression, and is further reduced significantly by the introduction of a forward-recursive formula. Based on the properties of the PRESS statistic, the proposed algorithm can achieve a fully automated procedure without resort to any other validation data set for iterative model evaluation. Numerical examples are used to demonstrate the efficacy of the algorithm.

On the F-word: a corpus-based analysis of the media representation of Feminism in British and German press discourse,1990-2009

Research in social psychology has shown that public attitudes towards feminism are mostly based on stereotypical views linking feminism with leftist politics and lesbian orientation. It is claimed that such attitudes are due to the negative and sexualised media construction of feminism. Studies concerned with the media representation of feminism seem to confirm this tendency. While most of this research provides significant insights into the representation of feminism, the findings are often based on a small sample of texts. Also, most of the research was conducted in an Anglo-American setting. This study attempts to address some of the shortcomings of previous work by examining the discourse of feminism in a large corpus of German and British newspaper data. It does so by employing the tools of Corpus Linguistics. By investigating the collocation profiles of the search term feminism, we provide evidence of salient discourse patterns surrounding feminism in two different cultural contexts.

Reticent autobiography: Henry Green and Christopher Isherwood at the Hogarth Press

Christopher Isherwood’s Lions and Shadows (1938) and Henry Green’s Pack My Bag (1940) are accounts of the authors’ educations in the 1920s. Published by Leonard and Virginia Woolf’s Hogarth Press, these works use reticent narrators to test the limits of autobiography. In each case, authorial self-presentation complicates the work’s classification in the literary marketplace: Green paradoxically extends his use of a pseudonym to autobiography and Isherwood assigns his own name to his purportedly fictional protagonist, and yet Hogarth published both as novels. The two texts and their publication histories exemplify modernist autobiography’s blurring of the lines between fiction and personal history.

Intersections and differentiations: a corpus-assisted discourse study of gender representations in the British press before, during and after the London Olympics 2012

This study examines the impact of a global sports event on gender representations in media reporting. Whereas previous research on gender, sport and media has been mainly concerned with sports events in the North American or Australian context, this study investigates the British media reporting before, during and after the London Olympics 2012. Our study follows the approach of Corpus-Assisted Discourse Studies (CADS) and uses both quantitative and qualitative research procedures. The results reveal more balanced gender representations during the London Olympics in that the ‘regular’ biased associations were supressed in favour of positive references to female achievements. However, little carry-though of the ‘gains’ was noted. Also, this study shows that the positive associations intersected with national sentiments and were used to celebrate the nation-state. At the same time, some subtle resistance was observed to accepting as ‘truly’ British the non-white athletes and those not born in Britain.