… transformations and optimizations for programs and become … in the induced product graph
based on similarities of its … racterization for hardware and software optimization efficiency. A …

… was analyzed using principal component analysis (PCA) to … necessary to use graph based
deep learning methods in this … To find optimized parameters in machine learning models, we …

… Abstract Optimization with nonnegative orthogonality constraints, which includes both … s in
machine learning and data science. Some typical instances of optimization with nonnegative …

… from 2010 to 2022 were retrieved for analysis. [Methods] The … path, compared and analyzed
the similarities and differences … [Limitations] The paper mainly summarized and analyzed the …

… in software programs. Bugs may seriously interfere with the … for further machine learning
(ML) based empirical software … The optimization strategy includes multiple parameter …

… Deep learning vulnerability detection method based on optimized inter-procedural semantics
of programs[J]. … Combining graph-based learning with automated data collection for …

… The fundamental aspect of the CPS is the analysis and evaluation of data from woody,
chal… sorting estimation [12] for the validation of programs. FlockStream focuses on a multi-operator …

… representative and practical graph-based SLAM algorithms. … Then, we analyze the performance
and power behaviors of … for parallel-executing programs with high efficiency. Therefore…

… of malware programs. Therefore, we propose a machine learning based malware analysis
… The results show that our system can effectively classify the unknown malware with a best …

… We reassemble these attributes into a new data set and then use the support vector machine
… Ince and TB Trafalis, “Kernel principal component analysis and support vector machines for …