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distributed randomized algorithm 10.1145/3465084.3467950

We present a distributed randomized algorithm that produces, with high probability, a maximal matching.

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distributed randomized algorithm 10.1155/2021/6643810

Second, we develop a distributed randomized algorithm SINR-Spanner to construct a required t-spanner with high probability.

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10.1109/IJCNN52387.2021.9533805

This work can be considered as the first step towards analyzing the variegated horizon of distributed randomized neural networks.

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10.1145/3465084.3467950

We present a distributed randomized algorithm that produces, with high probability, a maximal matching.

Full Text

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10.1155/2021/6643810

Second, we develop a distributed randomized algorithm SINR-Spanner to construct a required t-spanner with high probability.

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10.1109/INFOCOM42981.2021.9488917

We further propose low-complexity and myopic distributed randomized algorithms, and characterize their efficiency ratio.

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10.1007/S11432-020-2931-X

In this paper, we propose a distributed randomized algorithm for computing the weighted girth in weighted graphs with integral edge weights in the range [1, nc], where n is the number of vertices and c is a constant.

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10.1109/TCYB.2018.2890140

In this paper, a distributed randomized gradient-free optimization protocol of multiagent systems over weight-unbalanced digraphs described by row-stochastic matrices is proposed to solve a distributed constrained convex optimization problem.

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10.1007/S11276-018-01895-3

A replication-based distributed randomized algorithm is proposed, in which a balanced network status can be achieved after average operations among the nodes.

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Distributed Randomized

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Jul 04, 2022

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Distributed Randomized - This work can be considered as the first step towards analyzing the variegated horizon of distributed randomized neural networks. ^[1] We present a distributed randomized algorithm that produces, with high probability, a maximal matching. ^[2] Second, we develop a distributed randomized algorithm SINR-Spanner to construct a required t-spanner with high probability. ^[3] We further propose low-complexity and myopic distributed randomized algorithms, and characterize their efficiency ratio. ^[4] In this paper, we propose a distributed randomized algorithm for computing the weighted girth in weighted graphs with integral edge weights in the range [1, nc], where n is the number of vertices and c is a constant. ^[5] In this paper, a distributed randomized gradient-free optimization protocol of multiagent systems over weight-unbalanced digraphs described by row-stochastic matrices is proposed to solve a distributed constrained convex optimization problem. ^[6] A replication-based distributed randomized algorithm is proposed, in which a balanced network status can be achieved after average operations among the nodes. ^[7]

distributed randomized algorithm

We present a distributed randomized algorithm that produces, with high probability, a maximal matching. ^[1] Second, we develop a distributed randomized algorithm SINR-Spanner to construct a required t-spanner with high probability. ^[2] We further propose low-complexity and myopic distributed randomized algorithms, and characterize their efficiency ratio. ^[3] In this paper, we propose a distributed randomized algorithm for computing the weighted girth in weighted graphs with integral edge weights in the range [1, nc], where n is the number of vertices and c is a constant. ^[4] A replication-based distributed randomized algorithm is proposed, in which a balanced network status can be achieved after average operations among the nodes. ^[5]