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A Novel Variance Reduction Proximal Stochastic Newton Algorithm for Large-Scale Machine Learning Optimization Cover

A Novel Variance Reduction Proximal Stochastic Newton Algorithm for Large-Scale Machine Learning Optimization

International Journal of Advanced Network, Monitoring and Controls
Volume 9 (2024): Issue 4 (December 2024)
By: Mohammed Moyed Ahmed  
Open Access
|Dec 2024

Figures & Tables

Figure 1.

Convergence analysis for various algorithms
Convergence analysis for various algorithms

Figure 2.

Training Loss Vs Test accuracy chart for SVNR algorithm.
Training Loss Vs Test accuracy chart for SVNR algorithm.

Figure 3.

Computational time comparison for different algorithms
Computational time comparison for different algorithms
DOI: https://doi.org/10.2478/ijanmc-2024-0040 | Journal eISSN: 2470-8038
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Language: English
Page range: 84 - 90
Published on: Dec 31, 2024
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Composite optimization,
Machine learning,
Stochastic Newton method,
Variance reduction,
Convergence analysis
Related subjects:
Computer sciences,
Computer sciences, other

© 2024 Mohammed Moyed Ahmed, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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