Rapid and efficient bug assignment using ELM for IOT software
Y Yin, X Dong, T Xu - IEEE access, 2018 - ieeexplore.ieee.org
The reliable implementation of software in an Internet system directly influences information
transmission especially for the Internet of Things (IoT) system. Once defects in the system …
transmission especially for the Internet of Things (IoT) system. Once defects in the system …
Netki: a kirchhoff index based statistical graph embedding in nearly linear time
Recent advancements in learning from graph-structured data have shown promising results
on the graph classification task. However, due to their high time complexities, making them …
on the graph classification task. However, due to their high time complexities, making them …
Semi-supervised multi-graph classification using optimal feature selection and extreme learning machine
A multi-graph is represented by a bag of graphs. Semi-supervised multi-graph classification
is a partly supervised learning problem, which has a wide range of applications, such as bio …
is a partly supervised learning problem, which has a wide range of applications, such as bio …
Discriminative pattern discovery for the characterization of different network populations
Motivation An interesting problem is to study how gene co-expression varies in two different
populations, associated with healthy and unhealthy individuals, respectively. To this aim …
populations, associated with healthy and unhealthy individuals, respectively. To this aim …
Parallel multi-graph classification using extreme learning machine and MapReduce
A multi-graph is represented by a bag of graphs and modeled as a generalization of a multi-
instance. Multi-graph classification is a supervised learning problem, which has a wide …
instance. Multi-graph classification is a supervised learning problem, which has a wide …
Elm-based large-scale genetic association study via statistically significant pattern
Y Li, Y Zhao, G Wang, Z Wang… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Genetic association study (GAS) is a promising tool for detecting and analyzing the cause of
complex diseases. The extreme learning machine (ELM) has been successfully applied in a …
complex diseases. The extreme learning machine (ELM) has been successfully applied in a …
Super-graph classification based on composite subgraph features and extreme learning machine
A multi-graph is modeled as a bag of graphs, whose mutual relationships can be used to
enhance the accuracy of multi-graph classification. However, to the best of our knowledge …
enhance the accuracy of multi-graph classification. However, to the best of our knowledge …
Extreme learning machine for large-scale graph classification based on mapreduce
Z Wang, Y Zhao, Y Yuan, G Wang, L Chen - Neurocomputing, 2017 - Elsevier
Discriminative subgraph mining from a large collection of graph objects is a crucial problem
for graph classification. Several main memory-based approaches have been proposed to …
for graph classification. Several main memory-based approaches have been proposed to …
Big graph classification frameworks based on extreme learning machine
Graph data analysis is a hot topic in recent research area. Graph classification is one of the
most important graph data analysis problems, which choose the most probable class labels …
most important graph data analysis problems, which choose the most probable class labels …
Enhancing ELM by Markov boundary based feature selection
ELM, as an efficient classification technology, has been used in many popular application
domains. However, ELM has weak generalization performance when the data set is small …
domains. However, ELM has weak generalization performance when the data set is small …