In this work, we study the problem of online adaptive forecasting for locally stationary Time Varying Autoregressive processes (TVAR). The Normalized Mean Least Squares algorithm (NMLS) is an online stochastic gradient method which has been shown to perform efficiently, provided that the gradient step size is well chosen. This choice highly depends on the smoothness exponent of the evolving par...

Fraenkel and Simpson showed that the number of distinct squares in a word of length n is bounded from above by 2n, since at most two distinct squares have their rightmost, or last, occurrence begin at each position. Improvements by Ilie to 2n−Θ(logn) and by Deza et al. to ⌊11n/6⌋ rely on the study of combinatorics of FS-double-squares, when the maximum number of two last occurrences of squares ...

A well known result of Fraenkel and Simpson states that the number of distinct squares in a word of length n is bounded by 2n since at each position there are at most two distinct squares whose last occurrence start. In this paper, we investigate the problem of counting distinct squares in partial words, or sequences over a finite alphabet that may have some “do not know” symbols or “holes” (a ...

Synopsis The yield-line method of analysis provides a powerful means of identifying the ultimate load carrying capacity of reinforced concrete slabs. Benefits of the yield-line method are that it will often identify additional reserves of strength when applied to the analysis of existing slabs, and to highly economic slabs when used in design. Traditionally a hand-based method, the yield-line m...

Recent pragmatic accounts derive the ignorance inferences to which superlative modifiers give rise as quantity implicatures in a neo-Gricean framework. While these approaches successfully account for the interaction of at least with modals, the behavior of at most remains a puzzle. I propose that at most is composed of an antonymizing operator and at least and show how this accounts for the int...

fuzzy linear regression models are used to obtain an appropriate linear relation between a dependent variable and several independent variables in a fuzzy environment. several methods for evaluating fuzzy coefficients in linear regression models have been proposed. the first attempts at estimating the parameters of a fuzzy regression model used mathematical programming methods. in this the...