We present FeedbackGen, a system that uses a multi-adaptive approach to Natural Language Generation. With the term ‘multi-adaptive’, we refer to a system that is able to adapt its content to different user groups simultaneously, in our case adapting to both lecturers and students. We present a novel approach to student feedback generation, which simultaneously takes into account the preferences...

In modelling count data with multivariate predictors, we often encounter problems with clustering of observations and interdependency of predictors. We propose to use principal components of predictors to mitigate the multicollinearity problem and to abate information losses due to dimension reduction, a semiparametric link between the count dependent variable and the principal components is po...

In this paper we introduce a dynamic regression model that states how an output is related to an input allowing future values forecasting. The basic tools to set up this model are the orthogonal decomposition of a discrete time stochastic process by means of its principal components analysis, and the linear regression performed on the principal components of input and output processes. The beha...

Penelitian ini merupakan upaya pengembangan Model Output Statistics (MOS) yang akan digunakan sebagai alat kalibrasi prakiraan cuaca jangka pendek. Informasi mengenai akurat diharapkan dapat meminimalkan risiko kecelakaan disebabkan oleh cuaca, khususnya dalam bidang transportasi udara dan laut. Metode dikembangkan mencakup beberapa stasiun pengamatan di Indonesia. MOS sebuah metode berbasis re...

We show how to efficiently project a vector onto the top principal components of a matrix, without explicitly computing these components. Specifically, we introduce an iterative algorithm that provably computes the projection using few calls to any black-box routine for ridge regression. By avoiding explicit principal component analysis (PCA), our algorithm is the first with no runtime dependen...