Newton-Like Dynamics and Forward-Backward Methods for Structured Monotone Inclusions in Hilbert Spaces

Author:

Abbas B.,Attouch H.,Svaiter Benar F.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Management Science and Operations Research,Control and Optimization

Reference22 articles.

1. Peypouquet, J., Sorin, S.: Evolution equations for maximal monotone operators: asymptotic analysis in continuous and discrete time. J. Convex Anal. 17, 1113–1163 (2010)

2. Attouch, H., Svaiter, B.F.: A continuous dynamical Newton-like approach to solving monotone inclusions. SIAM J. Control Optim. 49, 574–598 (2011)

3. Attouch, H., Redont, P., Svaiter, B.F.: Global convergence of a closed-loop regularized Newton method for solving monotone inclusions in Hilbert spaces. J. Optim. Theory Appl. 157(3), 624–650 (2013)

4. Beck, A., Teboulle, M.: Gradient-based algorithms with applications in signal recovery problems. In: Palomar, D., Eldar, Y. (eds.) Convex Optimization in Signal Processing and Communications, pp. 33–88. Cambridge University Press, Cambridge (2010)

5. Combettes, P.L., Pesquet, J.-C.: Proximal splitting methods in signal processing. In: Bauschke, H., Burachik, R., Combettes, P.L., Elser, V., Luke, D.R., Wolkowicz, H. (eds.) Fixed-Point Algorithms for Inverse Problems in Science and Engineering, pp. 185–212. Springer, New York (2011)

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