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In this paper, we study diffusion social learning over weakly-connected graphs. We show that the asymmetric flow of information hinders the learning abilities of certain agents regardless of their local observations. Under some circumstances that we clarif ...
The ballistocardiogram (BCG) artifact is currently one of the most challenging in the EEG acquired concurrently with fMRI, with correction invariably yielding residual artifacts and/or deterioration of the physiological signals of interest. In this paper, ...
Compute-and-forward (CF) is a technique which exploits broadcast and superposition in wireless networks. In this paper, the CF energy benefit is studied for networks with unicast sessions and modeled by connected graphs. This benefit is defined as the rati ...
The topology of a mobile wireless network changes over time. Maintaining routes between all nodes requires the continuous transmission of control information, which consumes precious power and bandwidth resources. Many routing protocols have been developed ...
The JavaBIP framework allows the coordination of software components in an exogenous manner, while clearly separating the functional and coordination aspects of the system behaviour. JavaBIP implements the principles of the BIP component framework rooted i ...
Weighted undirected graphs are a simple, yet powerful way to encode structure in data. A first question we need to address regarding such graphs is how to use them effectively to enhance machine learning problems. A second but more important question is ho ...
A Kneser graph KG(n,k) is a graph whose vertices are in oneto-one correspondence with k -element subsets of [n], with two vertices connected if and only if the corresponding sets do not intersect. A famous result due to Lowisz states that the chromatic num ...
We consider the variation of Ramsey numbers introduced by Erdos and Pach [J. Graph Theory, 7 (1983), pp. 137-147], where instead of seeking complete or independent sets we only seek a t-homogeneous set, a vertex subset that induces a subgraph of minimum de ...
This paper examines the learning mechanism of adaptive agents over weakly connected graphs and reveals an interesting behavior on how information flows through such topologies. The results clarify how asymmetries in the exchange of data can mask local info ...
In this paper, we examine the learning mechanism of adaptive agents over weakly-connected graphs and reveal an interesting behavior on how information flows through such topologies. The results clarify how asymmetries in the exchange of data can mask local ...