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Self-adaptive gradient projection algorithms for variational inequalities involving non-Lipschitz continuous operators
In this paper, we introduce a self-adaptive inertial gradient projection algorithm for solving monotone or strongly pseudomonotone variational...
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Linesearch methods for bilevel split pseudomonotone variational inequality problems
In this paper, we propose Linesearch methods for solving a bilevel split variational inequality problem (BSVIP) involving a strongly monotone map**...
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New inertial algorithm for a class of equilibrium problems
The article introduces a new algorithm for solving a class of equilibrium problems involving strongly pseudomonotone bifunctions with a...
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Convergence rates of accelerated proximal gradient algorithms under independent noise
We consider an accelerated proximal gradient algorithm for the composite optimization with “independent errors” (errors little related with...
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Modified basic projection methods for a class of equilibrium problems
Projection methods are a popular class of methods for solving equilibrium problems. In this paper, we propose approximate one projection methods for...
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Iterative algorithms for solving fixed point problems and variational inequalities with uniformly continuous monotone operators
Using the double projection and Halpern methods, we prove two strong convergence results for finding a solution of a variational inequality problem...
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Strong convergence result for monotone variational inequalities
Our aim in this paper is to study strong convergence results for L -Lipschitz continuous monotone variational inequality but L is unknown using a...
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New self-adaptive step size algorithms for solving split variational inclusion problems and its applications
In this paper, we study a special instance of the split inverse problem (SIP), which is the split variational inclusion problem (SVIP). Three simple...
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Selective projection methods for solving a class of variational inequalities
Very recently, Gibali et al. (Optimization 66 , 417–437
2017 ) proposed a method, called selective projection method (SPM) in this paper, for solving... -
Convergence analysis of a new algorithm for strongly pseudomontone equilibrium problems
The paper introduces and analyzes the convergence of a new iterative algorithm for approximating solutions of equilibrium problems involving strongly...
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Approximately solving multi-valued variational inequalities by using a projection and contraction algorithm
A projection and contraction algorithm for solving multi-valued variational inequalities is proposed. The algorithm is proved to converge globally to...
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Generalized row-action methods for tomographic imaging
Row-action methods play an important role in tomographic image reconstruction. Many such methods can be viewed as incremental gradient methods for...
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Recovering Piecewise Smooth Multichannel Images by Minimization of Convex Functionals with Total Generalized Variation Penalty
We study and extend the recently introduced total generalized variation (TGV) functional for multichannel images. This functional has already been...
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On the Convergence of Primal–Dual Hybrid Gradient Algorithms for Total Variation Image Restoration
In this paper we establish the convergence of a general primal–dual method for nonsmooth convex optimization problems whose structure is typical in...
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Algorithms for the Split Variational Inequality Problem
We propose a prototypical Split Inverse Problem (SIP) and a new variational problem, called the Split Variational Inequality Problem (SVIP), which is...
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A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging
In this paper we study a first-order primal-dual algorithm for non-smooth convex optimization problems with known saddle-point structure. We prove...
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Accelerated Training of Max-Margin Markov Networks with Kernels
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M...
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Improved Human Parsing with a Full Relational Model
We show quantitative evidence that a full relational model of the body performs better at upper body parsing than the standard tree model, despite...
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Cutting-plane training of structural SVMs
Discriminative training approaches like structural SVMs have shown much promise for building highly complex and accurate models in areas like natural...
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Some Inexact Hybrid Proximal Augmented Lagrangian Algorithms
In this work, Solodov–Svaiter's hybrid projection-proximal and extragradient-proximal methods [16,17] are used to derive two algorithms to find a...