UNLocBoX

The UNLocboX is a matlab convex optimization toolbox part of the UnlocX project. It composed of the most used algorithms such as forward backward, Douglas-Rachford and ppxa. Moreover a all collection of proximal operators are available in order to implement problems very efficiently.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 262 articles )

Showing results 1 to 20 of 262.
Sorted by year (citations)

1 2 3 ... 12 13 14 next

  1. Abe, Jiro; Yamagishi, Masao; Yamada, Isao: Linearly involved generalized Moreau enhanced models and their proximal splitting algorithm under overall convexity condition (2020)
  2. Banert, Sebastian; Ringh, Axel; Adler, Jonas; Karlsson, Johan; Öktem, Ozan: Data-driven nonsmooth optimization (2020)
  3. Bertocchi, Carla; Chouzenoux, Emilie; Corbineau, Marie-Caroline; Pesquet, Jean-Christophe; Prato, Marco: Deep unfolding of a proximal interior point method for image restoration (2020)
  4. Bolte, Jérôme; Chen, Zheng; Pauwels, Edouard: The multiproximal linearization method for convex composite problems (2020)
  5. Brogliato, Bernard; Tanwani, Aneel: Dynamical systems coupled with monotone set-valued operators: formalisms, applications, well-posedness, and stability (2020)
  6. Deng, Zhao; Liu, Sanyang: Inertial proximal strictly contractive peaceman-Rachford splitting method with an indefinite term for convex optimization (2020)
  7. Erichson, N. Benjamin; Zheng, Peng; Manohar, Krithika; Brunton, Steven L.; Kutz, J. Nathan; Aravkin, Aleksandr Y.: Sparse principal component analysis via variable projection (2020)
  8. Hare, Warren; Planiden, Chayne; Sagastizábal, Claudia: A derivative-free (\mathcalV\mathcalU)-algorithm for convex finite-max problems (2020)
  9. Jiang, Fan; Wu, Zhongming; Cai, Xingju: Generalized ADMM with optimal indefinite proximal term for linearly constrained convex optimization (2020)
  10. Johnstone, Patrick R.; Eckstein, Jonathan: Projective splitting with forward steps only requires continuity (2020)
  11. Khan, Muhammad Aqeel Ahmad; Cholamjiak, Prasit: A multi-step approximant for fixed point problem and convex optimization problem in Hadamard spaces (2020)
  12. Li, Housen; Schwab, Johannes; Antholzer, Stephan; Haltmeier, Markus: NETT: solving inverse problems with deep neural networks (2020)
  13. Moharami, R.; Eskandani, G. Zamani: An extragradient algorithm for solving equilibrium problem and zero point problem in Hadamard spaces (2020)
  14. Molinari, Cesare; Peypouquet, Juan; Roldan, Fernando: Alternating forward-backward splitting for linearly constrained optimization problems (2020)
  15. O’Connor, Daniel; Vandenberghe, Lieven: On the equivalence of the primal-dual hybrid gradient method and Douglas-Rachford splitting (2020)
  16. Panahi, Ashkan; Chehreghani, Morteza Haghir; Dubhashi, Devdatt: Accelerated proximal incremental algorithm schemes for non-strongly convex functions (2020)
  17. Rasch, Julian; Chambolle, Antonin: Inexact first-order primal-dual algorithms (2020)
  18. Ryu, Ernest K.: Uniqueness of DRS as the 2 operator resolvent-splitting and impossibility of 3 operator resolvent-splitting (2020)
  19. Wang, Faqiang; Zhao, Cuicui; Liu, Jun; Huang, Haiyang: A variational image segmentation model based on normalized cut with adaptive similarity and spatial regularization (2020)
  20. Adcock, Ben; Gelb, Anne; Song, Guohui; Sui, Yi: Joint sparse recovery based on variances (2019)

1 2 3 ... 12 13 14 next