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We study Byzantine collaborative learning, where n nodes seek to collectively learn from each others' local data. The data distribution may vary from one node to another. No node is trusted, and f < n nodes can behave arbitrarily. We prove that collaborati ...
Starting with a randomly distributed sensor array with unknown sensor orientations, array calibration is needed before target localization and tracking can be performed using classical triangulation methods. In this paper, we assume that the sensors are on ...
A treatment is described for getting some algebro-geometric solutions of the coupled modified Kadomtsev-Petviashvili (cmKP) equations and a hierarchy of 1 + 1 dimensional integrable nonlinear evolution equations (INLEEs) by using the Neumann type systems t ...
This paper addresses the problem of atomic multicasting messages in asynchronous distributed systems. Firstly, we give a characterization of the notion of ``genuine atomic multicast''. This characterization leads to a better understanding of the difference ...
