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  1. Bounding the Inefficiency via the Primal-Dual Method

    The main tool used to show all the results in this book is the primal-dual method. Introduced by Bil`o [22], this framework is based on the...
    Vittorio Bilò, Cosimo Vinci in Co** with Selfishness in Congestion Games
    Chapter 2023
  2. Primal-Dual Simplex Method

    Methods perform very differently when solving the same problem. It is a common case that a problem that is solved slowly by the simplex method would...
    Chapter 2023
  3. Improved Approximation Algorithms by Generalizing the Primal-Dual Method Beyond Uncrossable Functions

    We address long-standing open questions raised by Williamson, Goemans, Vazirani and Mihail pertaining to the design of approximation algorithms for...

    Ishan Bansal, Joseph Cheriyan, ... Sharat Ibrahimpur in Algorithmica
    Article 20 May 2024
  4. Multi-consensus decentralized primal-dual fixed point algorithm for distributed learning

    Decentralized distributed learning has recently attracted significant attention in many applications in machine learning and signal processing. To...

    Kejie Tang, Weidong Liu, **aojun Mao in Machine Learning
    Article 08 April 2024
  5. Preconditioned golden ratio primal-dual algorithm with linesearch

    The golden ratio primal-dual algorithm (GRPDA) was proposed for solving the saddle point problems which are being widely used in a variety of areas....

    Shan Ma, Si Li, Feng Ma in Numerical Algorithms
    Article 16 April 2024
  6. Parallel Primal-dual Method with Application to Image Restoration

    As inverse problems, most image restoration algorithms involve linear inverse operator. When processing multichannel images, the inverse operation is...
    Chapter 2023
  7. A linear primal–dual multi-instance SVM for big data classifications

    Multi-instance learning (MIL) handles data that is organized into sets of instances known as bags. Traditionally, MIL is used in the...

    Lodewijk Brand, Hoon Seo, ... Hua Wang in Knowledge and Information Systems
    Article 26 August 2023
  8. A New Prediction–Correction Primal–Dual Hybrid Gradient Algorithm for Solving Convex Minimization Problems with Linear Constraints

    The primal–dual hybrid gradient (PDHG) algorithm has been applied for solving linearly constrained convex problems. However, it was shown that...

    Fahimeh Alipour, Mohammad Reza Eslahchi, Masoud Hajarian in Journal of Mathematical Imaging and Vision
    Article 24 February 2024
  9. A primal-dual splitting algorithm for composite monotone inclusions with minimal lifting

    In this work, we study resolvent splitting algorithms for solving composite monotone inclusion problems. The objective of these general problems is...

    Francisco J. Aragón-Artacho, Radu I. Boţ, David Torregrosa-Belén in Numerical Algorithms
    Article Open access 18 November 2022
  10. Primal–Dual Algorithms for Distributed Economic Dispatch

    In this chapter, we study a distributed primal–dual gradient algorithm applicable in a sequence of time-varying general directed networks based on a...
    Qingguo Lü, **aofeng Liao, ... Shanfu Gao in Distributed Optimization in Networked Systems
    Chapter 2023
  11. A Quasi-Newton Primal-Dual Algorithm with Line Search

    Quasi-Newton methods refer to a class of algorithms at the interface between first and second order methods. They aim to progress as substantially as...
    Shida Wang, Jalal Fadili, Peter Ochs in Scale Space and Variational Methods in Computer Vision
    Conference paper 2023
  12. Inertial accelerated primal-dual methods for linear equality constrained convex optimization problems

    In this paper, we propose an inertial accelerated primal-dual method for the linear equality constrained convex optimization problem. When the...

    **n He, Rong Hu, Ya-** Fang in Numerical Algorithms
    Article 08 January 2022
  13. \(O(1/k^2)\) convergence rates of (dual-primal) balanced augmented Lagrangian methods for linearly constrained convex programming

    The recent balanced augmented Lagrangian method (ALM) and its dual-primal version are effective for solving linearly constrained convex programming...

    Tao Zhang, Yong **a, Shiru Li in Numerical Algorithms
    Article 11 March 2024
  14. Improved Lattice Enumeration Algorithms by Primal and Dual Reordering Methods

    The security of lattice-based cryptosystems is generally based on the hardness of the Shortest Vector Problem (SVP). There are two common categories...
    Kazuki Yamamura, Yuntao Wang, Eiichiro Fujisaki in Information Security and Cryptology – ICISC 2021
    Conference paper 2022
  15. Dual Deficient-Basis Method

    This chapter attacks the standard LP problem from the dual side using the deficient basis. To achieve optimality, the method presented in the...
    Chapter 2023
  16. An MP-DWR method for h-adaptive finite element methods

    In a dual-weighted residual method based on the finite element framework, the Galerkin orthogonality is an issue that prevents solving the dual...

    Chengyu Liu, Guanghui Hu in Numerical Algorithms
    Article 27 May 2023
  17. Linear Programming Computation

    This monograph represents a historic breakthrough in the field of linear programming (LP)since George Dantzig first discovered the simplex method in...

    **-Qi PAN
    Book 2023
  18. Duality Principle and Dual Simplex Method

    Duality is an essential part of LP theory. It is related to the special relationship between one LP problem and another, both of which involve the...
    Chapter 2023
  19. A first-order inexact primal-dual algorithm for a class of convex-concave saddle point problems

    In this paper, we study a first-order inexact primal-dual algorithm (I-PDA) for solving a class of convex-concave saddle point problems. The I-PDA,...

    Fan Jiang, Zhongming Wu, ... Hongchao Zhang in Numerical Algorithms
    Article 16 March 2021
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