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We propose a novel method for drift estimation of multiscale diffusion processes when a sequence of discrete observations is given. For the Langevin dynamics in a two-scale potential, our approach relies on the eigenvalues and the eigenfunctions of the hom ...
This paper demonstrates the use of new processor instructions VPMADD, intended to appear in the coming generation of Intel processors (codename "Cannon Lake"), in order to accelerate the newly proposed key encapsulation mechanism (KEM) named SIKE. SIKE is ...
Data cleaning has become an indispensable part of data analysis due to the increasing amount of dirty data. Data scientists spend most of their time preparing dirty data before it can be used for data analysis. Existing solutions that attempt to automate t ...
The paper “Dynamic efficiency in multilayer transportation networks” (Bellocchi, Geroliminis, 2018) [1] introduced new performance measures to quantify dynamically the effect of traffic congestion in a multilayer network. Based on these measures, we explor ...
Percolation, in its most general interpretation, refers to the “flow” of something (a physical agent, data or information) in a network, possibly accompanied by some nonlinear dynamical processes on the network nodes (sometimes denoted reaction–diffusion s ...
Advances in data acquisition technologies and supercomputing for large-scale simulations have led to an exponential growth in the volume of spatial data. This growth is accompanied by an increase in data complexity, such as spatial density, but also by mor ...
Localizing the source of an epidemic is a crucial task in many contexts, including the detection of malicious users in social networks and the identification of patient zeros of disease outbreaks. The difficulty of this task lies in the strict limitation ...
We consider a distributed social learning problem where a network of agents is interested in selecting one among a finite number of hypotheses. The data collected by the agents might be heterogeneous, meaning that different sub-networks might observe data ...
Today organizations are more than ever complex systems. They are large, ramified, distributed, and intertwined so that their organic structure seems like a tangle of activities. Day by day individuals contribute to keep these structures alive with their wo ...
The discovery of patterns using a minimal set of assumptions constitutes a central challenge in the modeling of polyphonic music and complex streams in general. Skipgrams have been found to be a powerful model for capturing semi-local dependencies in seque ...
