This study investigates the topological form of a network and its impact on the uncertainty entrenched in descriptive measures computed from observed social network data, given ubiquitous data-error. We investigate what influence a network’s topology, in conjunction with the type and amount of error, has on the ability of a measure, derived from observed data, to correctly approximate the same ...

Manifold learning algorithms rely on a neighbourhood graph to provide an estimate of the data’s local topology. Unfortunately, current methods for estimating local topology assume local Euclidean geometry and locally uniform data density, which often leads to poor data embeddings. We address these shortcomings by proposing a framework that combines local learning with parametric density estimat...

Mass-spring systems are of special interest for soft tissue modeling in surgical simulation due to their ease of implementation and real-time behavior. However, the parameter identification (masses, spring constants, mesh topology) still remains a challenge. In previous work, we proposed an approach based on the training of mass-spring systems according to known reference models. Our initial fo...

Feedback stabilization of an ensemble of non interacting half spins described by Bloch equations is considered. This system may be seen as a prototype for infinite dimensional systems with continuous spectrum. We propose an explicit feedback law that stabilizes asymptotically the system around a uniform state of spin +1/2 or -1/2. The proof of the convergence is done locally around the equilibr...

The main concern of this article is to study Ulam stability of the set of ε-approximate minima of a proper lower semicontinuous convex function bounded below on a real normed space X, when the objective function is subjected to small perturbations (in the sense of Attouch & Wets). More precisely, we characterize the class all proper lower semicontinuous convex functions bounded below such that ...

This paper departs from traditional calibration in the sense that the pixels forming the camera have a completely unknown topology. Previous works have shown that the statistical properties of natural scenes, and a uniform motion of a camera both in translation and rotation, allow determining the topology of a central camera [10, 6]. Here we show that there is a quasi-linear relationship betwee...

Hybrid systems with memory refer to dynamical systems exhibiting both hybrid and delay phenomena. While systems of this type are frequently encountered in many physical and engineering systems, particularly in control applications, various issues centered around the robustness of hybrid delay systems have not been adequately dealt with. In this paper, we establish some basic results on a framew...

On the Twitter platform, an effective followee recommendation system is helpful to connecting users in a satisfactory manner. Topological relations and tweets content are two main factors considered in a followee recommendation system. However, how to combine these two kinds of information in a uniform framework is still an open problem. In this paper, we propose to combine deep learning techni...