Typically, an optimal smoothing parameter in a penalized spline regression is determined by minimizing an information criterion, such as one of the Cp, CV and GCV criteria. Since an explicit solution to the minimization problem for an information criterion cannot be obtained, it is necessary to carry out an iterative procedure to search for the optimal smoothing parameter, i.e., a grid search m...

The training of Neural Networks and particularly Multi-Layer Perceptrons (MLP's) is made by minimizing an error function usually known as "cost function". In our previous works, we apply the Error Entropy Minimization (EEM) algorithm in classification and its optimized version using, as cost function, the entropy of the errors between the outputs and the desired targets of the neural network. O...

Abstract. The naive Bayes text classifier has long been a core technique in information retrieval and, more recently, it has emerged as a focus of research itself in machine learning. This paper is concerned with the naive Bayes text classifier in its multinomial model instantiation. This model and an “equivalent” reversed version proposed here are interpreted under the statistical framework of...

We examine a test of a nonparametric regression function based on penalized spline smoothing. We show that, similarly to a penalized spline estimator, the asymptotic power of the penalized spline test falls into a small- K or a large-K scenarios characterized by the number of knots K and the smoothing parameter. However, the optimal rate of K and the smoothing parameter maximizing power for tes...

Although Hidden Markov Model based speech synthesis has been proved to have good performance, there are still some factors which degrade the quality of synthesized speech: vocoder, model accuracy and over-smoothing. This paper analyzes these factors separately. Modifications for removing different factors are proposed. Experimental results show that over-smoothing in frequency domain mainly aff...

We propose a new class of non-linear image recovery operators based on local smoothing applied both in the spatial domain (horizontal smoothing) and in the gray-level domain (vertical smoothing). The commonly used horizontal smoothing gives the way of reducing the noise level (noise filtering), whereas the vertical smoothing yields the edge preservation property. The method is indexed by a real...

Abstract Cyclic lattices and ideal were introduced by Micciancio (2002), Lyubashevsky (2006), respectively, which play an efficient role in Ajtai’s construction of a collision resistant Hash function (see Ajtai (1996), Dwork (1997)) Gentry’s fully homomorphic encryption Gentry (2009)). Let $$R=Z[x]/\langle \phi (x)\rangle $$ <...