Distributed nonconvex constrained optimization over time-varying digraphs-Reference-Cited by-同舟云学术

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Distributed nonconvex constrained optimization over time-varying digraphs

Published:2019-02-16 Issue:1-2 Volume:176 Page:497-544
ISSN:0025-5610
Container-title:Mathematical Programming
language:en
Short-container-title:Math. Program.

Author:

Scutari Gesualdo^ORCID,Sun Ying

Funder

Division of Computing and Communication Foundations

Division of Electrical, Communications and Cyber Systems

Office of Naval Research Global

Publisher

Springer Science and Business Media LLC

Subject

General Mathematics,Software

Link

http://link.springer.com/content/pdf/10.1007/s10107-018-01357-w.pdf

Reference54 articles.

1. Ahn, M., Pang, J., Xin, J.: Difference-of-convex learning: directional stationarity, optimality, and sparsity. SIAM J. Optim. 27(3), 1637–1665 (2017). https://doi.org/10.1137/16M1084754

2. Bertsekas, D.P.: Nonlinear Programming, 2nd edn. Athena Scientific, Belmont (1999)

3. Bertsekas, D.P., Tsitsiklis, J.N.: Gradient convergence in gradient methods with errors. SIAM J. Optim. 10(3), 627–642 (2000)

4. Bianchi, P., Jakubowicz, J.: Convergence of a multi-agent projected stochastic gradient algorithm for non-convex optimization. IEEE Trans. Autom. Control 58(2), 391–405 (2013)

5. Bild, A.H., et al.: Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature 439(7074), 353 (2006)

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