• NIMBUS

  • Referenced in 63 articles [sw04339]
  • NIMBUS, an interactive method for nondifferentiable multiobjective optimization problems, is described. The algorithm is based ... solved by an MPB (Multiobjective Proximal Bundle) method. The MPB method is a generalization ... Kiwiel’s proximal bundle approach for nondifferentiable single objective optimization into the multiobjective case ... treated individually without employing any scalarization. The method is capable of handling several nonconvex locally...
  • SDPNAL+

  • Referenced in 43 articles [sw13239]
  • methods based codes: (1) an alternating direction method of multipliers based solver called SDPAD ... easy-block-decomposition hybrid proximal extragradient method called 2EBD-HPE by R. Monteiro...
  • PESTO

  • Referenced in 30 articles [sw20864]
  • first-order methods for composite convex optimization, including those performing explicit, projected, proximal, conditional ... variants of fast proximal gradient, conditional gradient, subgradient and alternating projection methods. In particular ... analytical worst-case guarantee for the proximal point algorithm that is twice better than previously ... fast as the standard accelerated proximal gradient method...
  • MPBNGC

  • Referenced in 20 articles [sw11891]
  • Multiobjective proximal bundle method for nonconvex nonsmooth optimization: Fortran subroutine MPBNGC 2.0. MPBNGC ... multiobjective proximal bundle method for nonconvex, nonsmooth (nondifferentiable) and generally constrained minimization. The software...
  • PBNCGC

  • Referenced in 20 articles [sw06156]
  • solver PBNCGC: MPBNGC is a multiobjective proximal bundle method for nonconvex, nonsmooth (nondifferentiable) and generally...
  • SLEP

  • Referenced in 39 articles [sw13487]
  • order black-box methods. 3) Efficient Projection. The projection problem (proximal operator) can be solved...
  • AdaGrad

  • Referenced in 120 articles [sw22202]
  • present a new family of subgradient methods that dynamically incorporate knowledge of the geometry ... stochastic optimization and online learning which employ proximal functions to control the gradient steps ... provably as good as the best proximal function that can be chosen in hindsight ... theoretical analysis and show that adaptive subgradient methods outperform state...
  • ParNes

  • Referenced in 12 articles [sw08366]
  • rely on Nesterov’s accelerated proximal gradient method, which takes $O(sqrt {1/varepsilon })$ iterations...
  • clue

  • Referenced in 15 articles [sw09497]
  • computing on these, including methods for measuring proximity and obtaining consensus and ”secondary” clusterings...
  • IMRO

  • Referenced in 8 articles [sw20465]
  • IMRO: A proximal quasi-Newton method for solving ℓ 1 -regularized least squares problems ... present a proximal quasi-Newton method in which the approximation of the Hessian ... structure enables us to effectively recover the proximal point. The algorithm is applied...
  • GAP

  • Referenced in 18 articles [sw26294]
  • corresponding proximity matrices, for variables and subjects. Various matrix permutation algorithms and clustering methods with ... proximity matrices. It is more powerful and effective than conventional graphical methods when dimension reduction...
  • SpicyMKL

  • Referenced in 8 articles [sw14765]
  • SpicyMKL can be viewed as a proximal minimization method and converges super-linearly. The cost...
  • BlockPDPS.jl

  • Referenced in 3 articles [sw39173]
  • Julia package BlockPDPS.jl: Primal-dual block-proximal splitting for a class of non-convex problems ... nonlinear Lipschitz-differentiable operator (K). Our methods ... refinements of the nonlinear primal-dual proximal splitting method for such problems without the block ... based on the primal-dual proximal splitting method of Chambolle and Pock for convex problems...
  • McIPM

  • Referenced in 11 articles [sw07097]
  • self-regular proximity based feasible IPMs. Self-regular based interior point methods present a unified ... Regular proximity based approach allows to improve the performance of interior point method software when...
  • 2EBD-HPE

  • Referenced in 14 articles [sw31879]
  • Block-Decomposition (BD) method based on the BD-hybrid proximal extra-gradient. The main contribution ... scaling factor to balance the blocks. The method is used to solve four broad classes...
  • PNOPT

  • Referenced in 2 articles [sw20469]
  • MATLAB package that uses proximal Newton-type methods to minimize composite functions. For details, please ... arxiv.org/abs/1206.1623: Proximal Newton-type methods for minimizing composite functions. We generalize Newton-type methods ... show that the resulting proximal Newton-type methods inherit the desirable convergence behavior of Newton ... learning are special cases of proximal Newton-type methods, and our analysis yields new convergence...
  • NSOLIB

  • Referenced in 4 articles [sw07874]
  • with single or multiple objective functions. The methods are able to handle either simple bounds ... NSOLIB subroutines are implementations of the proximal bundle method. They have been tested with various...
  • ProxSARAH

  • Referenced in 4 articles [sw35438]
  • step making them different from existing nonconvex proximal-type algorithms. The algorithms only require ... order oracle. One key step of our methods is the new constant and dynamic step ... size is much larger than existing methods including proximal SVRG scheme in the single sample...
  • POGS

  • Referenced in 9 articles [sw26997]
  • POGS (Proximal Operator Graph Solver) is a solver for convex optimization problems in graph form ... using Alternating Direction Method of Multipliers (ADMM...
  • iPiano

  • Referenced in 51 articles [sw09623]
  • iPiano: inertial proximal algorithm for nonconvex optimization. In this paper we study an algorithm ... nonsmooth split version of the Heavy-ball method from Polyak. A rigorous analysis...