Zobrazeno 1 - 10
of 1 160
pro vyhledávání: '"Centorrino, A"'
We analyze the convergence behavior of \emph{globally weakly} and \emph{locally strongly contracting} dynamics. Such dynamics naturally arise in the context of convex optimization problems with a unique minimizer. We show that convergence to the equi
Externí odkaz:
http://arxiv.org/abs/2403.07572
Publikováno v:
Journal of Applied Econometrics, 2023
Improving the productivity of the agricultural sector is part of one of the Sustainable Development Goals set by the United Nations. To this end, many international organizations have funded training and technology transfer programs that aim to promo
Externí odkaz:
http://arxiv.org/abs/2312.13939
We propose and analyze a continuous-time firing-rate neural network, the positive firing-rate competitive network (\pfcn), to tackle sparse reconstruction problems with non-negativity constraints. These problems, which involve approximating a given i
Externí odkaz:
http://arxiv.org/abs/2311.03821
In this article, we provide a novel and broadly-applicable contraction-theoretic approach to continuous-time time-varying convex optimization. For any parameter-dependent contracting dynamics, we show that the tracking error is asymptotically proport
Externí odkaz:
http://arxiv.org/abs/2305.15595
This paper investigates stability conditions of continuous-time Hopfield and firing-rate neural networks by leveraging contraction theory. First, we present a number of useful general algebraic results on matrix polytopes and products of symmetric ma
Externí odkaz:
http://arxiv.org/abs/2302.13452
Autor:
Bilotta, Giuseppe, Zago, Vito, Centorrino, Veronica, Dalrymple, Robert A., Hérault, Alexis, Del Negro, Ciro, Saikali, Elie
Implicit integration of the viscous term can significantly improve performance in computational fluid dynamics for highly viscous fluids such as lava. We show improvements over our previous proposal for semi-implicit viscous integration in Smoothed P
Externí odkaz:
http://arxiv.org/abs/2206.14780
This paper is concerned with the modeling and analysis of two of the most commonly used recurrent neural network models (i.e., Hopfield neural network and firing-rate neural network) with dynamic recurrent connections undergoing Hebbian learning rule
Externí odkaz:
http://arxiv.org/abs/2204.05382
A supervised machine learning algorithm determines a model from a learning sample that will be used to predict new observations. To this end, it aggregates individual characteristics of the observations of the learning sample. But this information ag
Externí odkaz:
http://arxiv.org/abs/2202.08977
This paper considers identification and estimation of the causal effect of the time Z until a subject is treated on a survival outcome T. The treatment is not randomly assigned, T is randomly right censored by a random variable C and the time to trea
Externí odkaz:
http://arxiv.org/abs/2201.10826
Publikováno v:
European Journal of Innovation Management, 2022, Vol. 26, Issue 7, pp. 65-85.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/EJIM-07-2022-0362
