We extend the automata-theoretic framework for reasoning about infinitestate sequential systems to handle also the global model-checking problem. Our framework is based on the observation that states of such systems, which carry a finite but unbounded amount of information, can be viewed as nodes in an infinite tree, and transitions between states can be simulated by finite-state automata. Chec...

Many real-life applications consider nominal categorical predictor variables that have a hierarchical structure, e.g. economic activity data in Official Statistics. In this paper, we focus on linear regression models built the presence of type variables, and study consolidation their categories to better tradeoff between interpretability fit model data. We propose so-called Tree based Linear Re...

Simulated landscapes have been used for decades to evaluate search strategies whose goal is to find the landscape location with maximum fitness. Understanding properties of landscapes is important for understanding search difficulty. This paper presents a novel and transparent characterization of NK landscapes and derives an analytic expression representing the expected number of local optima. ...

This work considers the problem of learning the structure of multivariate linear tree models, whichinclude a variety of directed tree graphical models with continuous, discrete, and mixed latent variablessuch as linear-Gaussian models, hidden Markov models, Gaussian mixture models, and Markov evolu-tionary trees. The setting is one where we only have samples from certain observe...

facial expressions are the most powerful and direct means of presenting human emotions and feelings and offer a window into a persons’ state of mind. in recent years, the study of facial expression and recognition has gained prominence; as industry and services are keen on expanding on the potential advantages of facial recognition technology. as machine vision and artificial intelligence advan...

this paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. this estimation method is obtained by implementing ridge regression learning algorithm in the la- grangian dual space. the distance measure for fuzzy numbers that suggested by diamond is used and the local linear smoothing technique with the cross- validation procedure for selecting t...