An inexact proximal augmented Lagrangian framework with arbitrary linearly convergent inner solver for composite convex optimization

Author:

Li Fei,Qu Zheng

Publisher

Springer Science and Business Media LLC

Subject

Software,Theoretical Computer Science

Reference51 articles.

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2. Allen-Zhu, Z.: Katyusha: the first direct acceleration of stochastic gradient methods. J. Mach. Learn. Res. 18(1), 8194–8244 (2017)

3. Auslender, A., Teboulle, M.: Interior projection-like methods for monotone variational inequalities. Math. Program. 104(1), 39–68 (2005). https://doi.org/10.1007/s10107-004-0568-x

4. Beck, A., Teboulle, M.: A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J. Imaging Sci. 2(1), 183–202 (2009)

5. Beck, A., Teboulle, M.: Smoothing and first order methods: a unified framework. SIAM J. Optim. 22(2), 557–580 (2012). https://doi.org/10.1137/100818327

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