Many real-world networks are described by both connectivity information and features for every node. To better model and understand these networks, we present structure preserving metric learning (SPML), an algorithm ...
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ISBN:
(纸本)9781618395993
Many real-world networks are described by both connectivity information and features for every node. To better model and understand these networks, we present structure preserving metric learning (SPML), an algorithm for learning a Mahalanobis distance metric from a network such that the learned distances are tied to the inherent connectivity structure of the network. Like the graph embedding algorithm structure preserving embedding, SPML learns a metric which is structure preserving, meaning a connectivity algorithm such as k-nearest neighbors will yield the correct connectivity when applied using the distances from the learned metric. We show a variety of synthetic and real-world experiments where SPML predicts link patterns from node features more accurately than standard techniques. We further demonstrate a method for optimizing SPML based on stochastic gradient descent which removes the running-time dependency on the size of the network and allows the method to easily scale to networks of thousands of nodes and millions of edges.
In this paper, a distributed PSO algorithm in the JADE platform is studied based on traditional PSO. A parallel PSO algorithm structure based on Multi-agent corporative is proposed. The structure is made tip of severa...
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ISBN:
(纸本)9780769533575
In this paper, a distributed PSO algorithm in the JADE platform is studied based on traditional PSO. A parallel PSO algorithm structure based on Multi-agent corporative is proposed. The structure is made tip of several compute units. Each unit is a compute agent running basic particles swarm optimization. Simulation results show that the distributed structure can enhance system running efficiency. With the principal and subordinate running mechanism, the communication step is simplified, the running efficiency is optimized and the realization speed is enhanced.
A theory of the structural composition of an alilorithm is presented which allows the frequencies of occurrence of the individual operators and operands to be estimated. It provides justification for some recent hypot...
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