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Musca Optimizer: A Perturbation-Based Escape Algorithm for Gradient Descent
Authors
1 Syncaissa Systems Inc. USA.
Article Information
- Published In
- Volume 5, Issue 6 (2025)
- Published Online
- November-December 2025
- Pages
- 59-65
- Article Type
- Original Article
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References
1. S. Ruder, An overview of gradient descent optimization algorithms, arXiv preprint arXiv: 1609.04747, 2016.
2. S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, Optimization by simulated annealing, Science, vol. 220, no. 4598, pp. 671 680, 1983.
3. J. Kennedy and R. Eberhart, Particle swarm optimization, in Proceedings of ICNN'95, vol. 4, pp. 1942 1948, IEEE, 1995.
4. D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning. Addison- Wesley, 1989.
5. L. Bottou, Large-scale machine learning with stochastic gradient descent, in Proceedings of COMPSTAT'2010, pp. 177 186, Springer, 2010.
2. S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, Optimization by simulated annealing, Science, vol. 220, no. 4598, pp. 671 680, 1983.
3. J. Kennedy and R. Eberhart, Particle swarm optimization, in Proceedings of ICNN'95, vol. 4, pp. 1942 1948, IEEE, 1995.
4. D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning. Addison- Wesley, 1989.
5. L. Bottou, Large-scale machine learning with stochastic gradient descent, in Proceedings of COMPSTAT'2010, pp. 177 186, Springer, 2010.
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