Gradient descent for quadratic functions using geometric mean and the Kai Fang method

Author:

Rim KwangCheol1ORCID,Kim Pankoo2,Ko Hoon3ORCID

Affiliation:

1. College of Basic & General Education Dongsin University Seoul South Korea

2. Department of Computer Engineering Chosun University Gwangju South Korea

3. Research Institute for Computer and Information Communication (RICIC) Chungbuk National University Cheongju‐si South Korea

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Reference14 articles.

1. SGD‐QN: careful Quasi‐Newton stochastic gradient descent;Bordes A;J Mach Learn Res,2009

2. Trust region Newton method for large‐scale logistic regression;Lin C‐J;J Mach Learn Res,2008

3. Advances in optimizing recurrent networks

4. Clarkson Kenneth Lee. Algorithms for Closest‐Point Problems (Computational Geometry). Diss. Stanford University 1985.

5. Abadi M Agarwal A Barham P et al. Tensorflow: large‐scale machine learning on heterogeneous distributed systems; 2016. arXiv preprint arXiv:1603.04467.

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