Functional mixed-effects models are very useful in analyzing functional data. A general functional mixed-effects model that inherits the flexibility of linear mixed-effects model...
This paper aims to improve the accuracy of query result-size estimations in query optimizers by leveraging the dynamic feedback obtained from observations on the executed query wo...
Abstract. In this paper, we present self-avoiding walks as a novel technique to linearize" a triangular mesh. Unlike space- lling curves which are based on a geometric embeddi...
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
Background: Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads ...