Sampling method and device of target full-connection subgraph and electronic equipment
A sampling device, fully connected technology, applied in the field of deep learning, can solve problems such as large space, inability to efficiently improve the efficiency of fully connected subgraphs, and low probability
Inactive Publication Date: 2022-03-22
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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However, due to the huge sample space to be sampled, the probability of directly using Gaussian Bose sampling to obtain the maximum weight fully connected subgraph is low, and the sampling probability can be increased through sampling post-processing, but the post-processing methods in related technologies are inefficient and cannot be efficient Improve the efficiency of obtaining the maximum weight fully connected subgraph through sampling
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[0021] Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
[0022] Artificial Intelligence (AI for short) is a technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. At present, AI technology has the advantages of high automation, high precision, and low cost, and has been widely used.
[0023] Deep learning (Deep Learning, ...
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The invention provides a sampling method and device of a target full-connection sub-graph and electronic equipment, and relates to the technical field of deep learning and the technical field of graph theory in the technical field of artificial intelligence. The method comprises the following steps: obtaining a plurality of historical full-connection sub-graphs and a first full-connection sub-graph, carrying out combination operation on the first full-connection sub-graph and the plurality of historical full-connection sub-graphs to generate a plurality of second full-connection sub-graphs, obtaining a full-connection sub-graph with the maximum weight from the plurality of second full-connection sub-graphs and the plurality of historical full-connection sub-graphs, and obtaining a full-connection sub-graph with the maximum weight from the plurality of second full-connection sub-graphs and the plurality of historical full-connection sub-graphs. The sub-graphs are used as target full-connection sub-graphs. The full-connection sub-graphs obtained after sampling are further post-processed in a combined operation mode, and the efficiency of obtaining the maximum-weight full-connection sub-graphs through sampling is more efficiently improved by fully utilizing historical information formed by historical full-connection sub-graphs.
Description
technical field [0001] The present disclosure relates to the technical field of deep learning and the technical field of graph theory in the technical field of artificial intelligence, and in particular to a sampling method, device and electronic equipment for a fully connected subgraph of a target. Background technique [0002] Bose sampling is a modern quantum optical algorithm with strong computing power. Its principle is to send the same photon into a quantum optical system, and use a photon counter to measure the output state of the quantum optical system. Gaussian Bose sampling is used as a glass The extension of color sampling is applied to solve graph combination problems, for example, Gaussian Bose sampling can be used to generate maximum weight fully connected subgraphs in weighted undirected graphs. However, due to the huge sample space to be sampled, the probability of directly using Gaussian Bose sampling to obtain the maximum weight fully connected subgraph is ...
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IPC IPC(8): G06T1/00G06T3/40
CPCG06T1/0007G06T3/4038G06T2207/20221G06T2200/32
Inventor 周景博郑书豪窦德景
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD