A double incremental aggregated gradient method with linear convergence rate for large-scale optimization

Aryan Mokhtari; Mert Gürbüzbalaban; Alejandro Ribeiro

doi:10.1109/ICASSP.2017.7953047

Publications · Conference paper · ICASSP 2017

A double incremental aggregated gradient method with linear convergence rate for large-scale optimization

Aryan Mokhtari, Mert Gürbüzbalaban, Alejandro Ribeiro

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4696–4700, 2017.

Publisher (DOI)

Topics

Incremental methods & data ordering

Cite

@inproceedings{mokhtari2017diag,
  title   = {A double incremental aggregated gradient method with linear convergence rate for large-scale optimization},
  author  = {Aryan Mokhtari and Mert Gürbüzbalaban and Alejandro Ribeiro},
  year    = {2017},
  booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages   = {4696--4700},
  doi     = {10.1109/ICASSP.2017.7953047},
}

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Randomness and permutations in coordinate descent methods (Math. Program., 2020)
Convergence rate of incremental gradient and incremental Newton methods (SIAM J. Optim., 2019)
Global convergence rate of proximal incremental aggregated gradient methods (SIAM J. Optim., 2018)
Surpassing gradient descent provably: a cyclic incremental method with linear convergence rate (SIAM J. Optim., 2018)

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