Gradient descent (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Gradient descent" in English language version.

refsWebsite

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11doi.org

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5arxiv.org

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4semanticscholar.org

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3nih.gov

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2web.archive.org

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2archive.org

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1uni-bielefeld.de

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1researchgate.net

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1mit.edu

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1quantamagazine.org

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1ucla.edu

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1siam.org

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1worldcat.org

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1psu.edu

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1willamette.edu

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1coursera.org

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1tlienart.github.io

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archive.org

Saad, Yousef (2003). Iterative methods for sparse linear systems (2nd ed.). Philadelphia, Pa.: Society for Industrial and Applied Mathematics. pp. 195. ISBN 978-0-89871-534-7.
Press, W. H.; Teukolsky, S. A.; Vetterling, W. T.; Flannery, B. P. (1992). Numerical Recipes in C: The Art of Scientific Computing (2nd ed.). New York: Cambridge University Press. ISBN 0-521-43108-5.

arxiv.org

Bernstein, Jeremy; Vahdat, Arash; Yue, Yisong; Liu, Ming-Yu (2020-06-12). "On the distance between two neural networks and the stability of learning". arXiv:2002.03432 [cs.LG].
Bouwmeester, Henricus; Dougherty, Andrew; Knyazev, Andrew V. (2015). "Nonsymmetric Preconditioning for Conjugate Gradient and Steepest Descent Methods". Procedia Computer Science. 51: 276–285. arXiv:1212.6680. doi:10.1016/j.procs.2015.05.241.
Kim, D.; Fessler, J. A. (2016). "Optimized First-order Methods for Smooth Convex Minimization". Mathematical Programming. 151 (1–2): 81–107. arXiv:1406.5468. doi:10.1007/s10107-015-0949-3. PMC 5067109. PMID 27765996. S2CID 207055414.
Drori, Yoel (2017). "The Exact Information-based Complexity of Smooth Convex Minimization". Journal of Complexity. 39: 1–16. arXiv:1606.01424. doi:10.1016/j.jco.2016.11.001. S2CID 205861966.
Combettes, P. L.; Pesquet, J.-C. (2011). "Proximal splitting methods in signal processing". In Bauschke, H. H.; Burachik, R. S.; Combettes, P. L.; Elser, V.; Luke, D. R.; Wolkowicz, H. (eds.). Fixed-Point Algorithms for Inverse Problems in Science and Engineering. New York: Springer. pp. 185–212. arXiv:0912.3522. ISBN 978-1-4419-9568-1.

coursera.org

Geoffrey Hinton; Nitish Srivastava; Kevin Swersky. "The momentum method". Coursera. Retrieved 2 October 2018. Part of a lecture series for the Coursera online course Neural Networks for Machine Learning Archived 2016-12-31 at the Wayback Machine.

doi.org

Courant, R. (1943). "Variational methods for the solution of problems of equilibrium and vibrations". Bulletin of the American Mathematical Society. 49 (1): 1–23. doi:10.1090/S0002-9904-1943-07818-4.
Curry, Haskell B. (1944). "The Method of Steepest Descent for Non-linear Minimization Problems". Quart. Appl. Math. 2 (3): 258–261. doi:10.1090/qam/10667.
Barzilai, Jonathan; Borwein, Jonathan M. (1988). "Two-Point Step Size Gradient Methods". IMA Journal of Numerical Analysis. 8 (1): 141–148. doi:10.1093/imanum/8.1.141.
Wolfe, Philip (April 1969). "Convergence Conditions for Ascent Methods". SIAM Review. 11 (2): 226–235. doi:10.1137/1011036.
Bouwmeester, Henricus; Dougherty, Andrew; Knyazev, Andrew V. (2015). "Nonsymmetric Preconditioning for Conjugate Gradient and Steepest Descent Methods". Procedia Computer Science. 51: 276–285. arXiv:1212.6680. doi:10.1016/j.procs.2015.05.241.
Ross, I.M. (July 2019). "An optimal control theory for nonlinear optimization". Journal of Computational and Applied Mathematics. 354: 39–51. doi:10.1016/j.cam.2018.12.044. S2CID 127649426.
Walkington, Noel J. (2023). "Nesterov's Method for Convex Optimization". SIAM Review. 65 (2): 539–562. doi:10.1137/21M1390037. ISSN 0036-1445.
Kim, D.; Fessler, J. A. (2016). "Optimized First-order Methods for Smooth Convex Minimization". Mathematical Programming. 151 (1–2): 81–107. arXiv:1406.5468. doi:10.1007/s10107-015-0949-3. PMC 5067109. PMID 27765996. S2CID 207055414.
Drori, Yoel (2017). "The Exact Information-based Complexity of Smooth Convex Minimization". Journal of Complexity. 39: 1–16. arXiv:1606.01424. doi:10.1016/j.jco.2016.11.001. S2CID 205861966.
Qian, Ning (January 1999). "On the momentum term in gradient descent learning algorithms". Neural Networks. 12 (1): 145–151. CiteSeerX 10.1.1.57.5612. doi:10.1016/S0893-6080(98)00116-6. PMID 12662723. S2CID 2783597.

dx.doi.org

Boyd, Stephen; Vandenberghe, Lieven (2004-03-08). Convex Optimization. Cambridge University Press. ISBN 978-0-521-83378-3.

mit.edu

dspace.mit.edu

Altschuler, Jason (Jason M. ) (2018). Greed, hedging, and acceleration in convex optimization (Thesis thesis). Massachusetts Institute of Technology.

nih.gov

pubmed.ncbi.nlm.nih.gov

Kim, D.; Fessler, J. A. (2016). "Optimized First-order Methods for Smooth Convex Minimization". Mathematical Programming. 151 (1–2): 81–107. arXiv:1406.5468. doi:10.1007/s10107-015-0949-3. PMC 5067109. PMID 27765996. S2CID 207055414.
Qian, Ning (January 1999). "On the momentum term in gradient descent learning algorithms". Neural Networks. 12 (1): 145–151. CiteSeerX 10.1.1.57.5612. doi:10.1016/S0893-6080(98)00116-6. PMID 12662723. S2CID 2783597.

ncbi.nlm.nih.gov

Kim, D.; Fessler, J. A. (2016). "Optimized First-order Methods for Smooth Convex Minimization". Mathematical Programming. 151 (1–2): 81–107. arXiv:1406.5468. doi:10.1007/s10107-015-0949-3. PMC 5067109. PMID 27765996. S2CID 207055414.

psu.edu

citeseerx.ist.psu.edu

Qian, Ning (January 1999). "On the momentum term in gradient descent learning algorithms". Neural Networks. 12 (1): 145–151. CiteSeerX 10.1.1.57.5612. doi:10.1016/S0893-6080(98)00116-6. PMID 12662723. S2CID 2783597.

quantamagazine.org

Parshall, Allison (August 11, 2023). "Risky Giant Steps Can Solve Optimization Problems Faster". Quanta Magazine. Retrieved August 11, 2023.

researchgate.net

Polyak, Boris (1987). Introduction to Optimization.

semanticscholar.org

api.semanticscholar.org

Ross, I.M. (July 2019). "An optimal control theory for nonlinear optimization". Journal of Computational and Applied Mathematics. 354: 39–51. doi:10.1016/j.cam.2018.12.044. S2CID 127649426.
Kim, D.; Fessler, J. A. (2016). "Optimized First-order Methods for Smooth Convex Minimization". Mathematical Programming. 151 (1–2): 81–107. arXiv:1406.5468. doi:10.1007/s10107-015-0949-3. PMC 5067109. PMID 27765996. S2CID 207055414.
Drori, Yoel (2017). "The Exact Information-based Complexity of Smooth Convex Minimization". Journal of Complexity. 39: 1–16. arXiv:1606.01424. doi:10.1016/j.jco.2016.11.001. S2CID 205861966.
Qian, Ning (January 1999). "On the momentum term in gradient descent learning algorithms". Neural Networks. 12 (1): 145–151. CiteSeerX 10.1.1.57.5612. doi:10.1016/S0893-6080(98)00116-6. PMID 12662723. S2CID 2783597.

siam.org

epubs.siam.org

Walkington, Noel J. (2023). "Nesterov's Method for Convex Optimization". SIAM Review. 65 (2): 539–562. doi:10.1137/21M1390037. ISSN 0036-1445.

tlienart.github.io

"Mirror descent algorithm".

ucla.edu

seas.ucla.edu

Vandenberghe, Lieven (2019). "Fast Gradient Methods" (PDF). Lecture notes for EE236C at UCLA.

uni-bielefeld.de

math.uni-bielefeld.de

Lemaréchal, C. (2012). "Cauchy and the Gradient Method" (PDF). Doc Math Extra: 251–254. Archived from the original (PDF) on 2018-12-29. Retrieved 2020-01-26.

web.archive.org

Lemaréchal, C. (2012). "Cauchy and the Gradient Method" (PDF). Doc Math Extra: 251–254. Archived from the original (PDF) on 2018-12-29. Retrieved 2020-01-26.
Geoffrey Hinton; Nitish Srivastava; Kevin Swersky. "The momentum method". Coursera. Retrieved 2 October 2018. Part of a lecture series for the Coursera online course Neural Networks for Machine Learning Archived 2016-12-31 at the Wayback Machine.

willamette.edu

"Momentum and Learning Rate Adaptation". Willamette University. Retrieved 17 October 2014.

worldcat.org

Walkington, Noel J. (2023). "Nesterov's Method for Convex Optimization". SIAM Review. 65 (2): 539–562. doi:10.1137/21M1390037. ISSN 0036-1445.