The idea of neighborhood construction emerged as an approach for improving the quality of the results of classifying and clustering algorithms. However, we think that a comprehensive study of the neighborhood construction algorithm is very useful. To the best of our knowledge, this is the first ...
JA-BE-JA: A distributed algorithm for balanced graph Partitioning 2013, International Conference on Self-Adaptive and Self-Organizing Systems, SASO A mltilevel memetic approach for improving graph k-partitions 2011, IEEE Transactions on Evolutionary Computation View all citing articles on ScopusView...
This glossary contains an annotated listing of some 300 parameters of graphs, together with their definitions, and, for most of these, a reference to the authors who introduced them. Let G = (V, E) be an undirected graph having order...
Severaldatabasesare used for Online Transaction Processing (OLTP) due to their reliability,scalability, and ability to handle high transaction volumes. Below are the most popular OLTP databases, but also those that support both OLTP and OLAP: Oracle Database. A robust relational database known for ...
(for a definition of relevancy). An algorithm that processes the whole graph (as opposed to localized information queries expressed with graph query languages seen previously) is typically executed in parallel fashion when the resources for parallelism are available. When implementing these algorithms, ...
RUN Ncut_test.m to determine the optimal partition from varied partitions (produced by Jianbo Shi's Normalized cuts). CVDD.mincludes Algorithm 1: CVDD in our paper. Ncut_test.mas an example includes Algorithm 2: CVDD-OP in our paper. ...
the total loss is dominated by the supervised loss term. As the training evolves, the unsupervised loss term plays a more important role. The optimization of the loss function in Eq.2is conducted using the SGD algorithm. In thetth iteration, the model parameters\(\Theta \)are updated with\...
This method first uses t-SNE to reduce the dimensionality of the dataset and combines the improved Apriori algorithm with the hypergraph construction method to construct a hypergraph for model clustering. Then, it employs the dense subgraph partition algorithm based on multi-level hypergraph ...
This study presents a novel algorithm for improving satellite images, called remote sensing image enhancement based on cluster enhancement (RSIECE). First, the input image is clustered by the algorithm of fuzzy semi-supervised clustering. Then, the upper bound and lower bound are estimated according...
Most implementation of algorithms do not scale to tens or hundreds of cores (let alone thousands or millions,) even if in theory the algorithm itself is reasonably easy to parallelize. The world’s fastest single machine (by a margin of 2x from the next competitor,) the Chinese Tianhe-2, ...