Advances in Asynchronous Parallel and Distributed Optimization
نویسندگان
چکیده
منابع مشابه
Parallel asynchronous particle swarm optimization.
The high computational cost of complex engineering optimization problems has motivated the development of parallel optimization algorithms. A recent example is the parallel particle swarm optimization (PSO) algorithm, which is valuable due to its global search capabilities. Unfortunately, because existing parallel implementations are synchronous (PSPSO), they do not make efficient use of comput...
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The Distributed Constraint Optimization Problem (DCOP) is able to model a wide variety of distributed reasoning tasks that arise in multiagent systems. Unfortunately, existing methods for DCOP are not able to provide theoretical guarantees on global solution quality while allowing agents to operate asynchronously. We show how this failure can be remedied by allowing agents to make local decisio...
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Network environments always can be invaded by intruder agents. In networks where nodes are performing some computations, intruder agents might contaminate some nodes. Therefore, problem of decontaminating a network infected by intruder agents is one of the major problems in these networks. In this paper, we present a distributed asynchronous local algorithm for decontaminating a network. In mos...
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This article presents an asynchronous algorithm for solving Distributed Constraint Optimization problems (DCOPs). The proposed technique unifies asynchronous backtracking (ABT) and asynchronous distributed optimization (ADOPT) where valued nogoods enable more flexible reasoning and more opportunities of communication, leading to an important speed-up. The concept of valued nogood is an extensio...
متن کاملAsynchronous Parallel Stochastic Gradient for Nonconvex Optimization
Asynchronous parallel implementations of stochastic gradient (SG) have been broadly used in solving deep neural network and received many successes in practice recently. However, existing theories cannot explain their convergence and speedup properties, mainly due to the nonconvexity of most deep learning formulations and the asynchronous parallel mechanism. To fill the gaps in theory and provi...
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ژورنال
عنوان ژورنال: Proceedings of the IEEE
سال: 2020
ISSN: 0018-9219,1558-2256
DOI: 10.1109/jproc.2020.3026619