Pages that link to "Item:Q128676"

The following pages link to Smooth minimization of non-smooth functions (Q128676):

Displaying 50 items.

• On max-\(k\)-sums (Q1785208) (← links)
• A simple algorithm for a class of nonsmooth convex-concave saddle-point problems (Q1785640) (← links)
• An efficient algorithm for sparse inverse covariance matrix estimation based on dual formulation (Q1796959) (← links)
• Flexible low-rank statistical modeling with missing data and side information (Q1799348) (← links)
• An algorithm to minimize the sum of a semi-smooth function and a \(C^ 1\) function (Q1908947) (← links)
• A first-order primal-dual algorithm for convex problems with applications to imaging (Q1932848) (← links)
• A fast fixed point algorithm for total variation deblurring and segmentation (Q1932946) (← links)
• Dynamic Lagrangian dual and reduced RLT constructs for solving \(0-1\) mixed-integer programs (Q1935886) (← links)
• Conjugate gradient type methods for the nondifferentiable convex minimization (Q1941196) (← links)
• Bregmanized domain decomposition for image restoration (Q1945371) (← links)
• Accelerated linearized Bregman method (Q1945379) (← links)
• Analysis of a new variational model to restore point-like and curve-like singularities in imaging (Q1946538) (← links)
• A double smoothing technique for solving unconstrained nondifferentiable convex optimization problems (Q1946618) (← links)
• A cyclic projected gradient method (Q1946620) (← links)
• Iteration-complexity of first-order penalty methods for convex programming (Q1949272) (← links)
• Fine tuning Nesterov's steepest descent algorithm for differentiable convex programming (Q1949275) (← links)
• Estimating networks with jumps (Q1950892) (← links)
• Neural network based on systematically generated smoothing functions for absolute value equation (Q2008074) (← links)
• On the convergence of the iterates of proximal gradient algorithm with extrapolation for convex nonsmooth minimization problems (Q2010091) (← links)
• Solving nearly-separable quadratic optimization problems as nonsmooth equations (Q2013144) (← links)
• Automated parameter selection for total variation minimization in image restoration (Q2014482) (← links)
• Point process estimation with Mirror Prox algorithms (Q2019904) (← links)
• Dynamic stochastic approximation for multi-stage stochastic optimization (Q2020613) (← links)
• Acceleration techniques for level bundle methods in weakly smooth convex constrained optimization (Q2023658) (← links)
• The distance between convex sets with Minkowski sum structure: application to collision detection (Q2023661) (← links)
• Optimizing the efficiency of first-order methods for decreasing the gradient of smooth convex functions (Q2026726) (← links)
• Acceleration of primal-dual methods by preconditioning and simple subproblem procedures (Q2027970) (← links)
• A dual reformulation and solution framework for regularized convex clustering problems (Q2029898) (← links)
• Nearly optimal first-order methods for convex optimization under gradient norm measure: an adaptive regularization approach (Q2031939) (← links)
• A phase model using the Huber norm for estimating point spread function under frozen flow hypothesis (Q2033091) (← links)
• Randomized smoothing variance reduction method for large-scale non-smooth convex optimization (Q2033403) (← links)
• An augmented memoryless BFGS method based on a modified secant equation with application to compressed sensing (Q2034433) (← links)
• Decentralized and parallel primal and dual accelerated methods for stochastic convex programming problems (Q2042418) (← links)
• Fast and safe: accelerated gradient methods with optimality certificates and underestimate sequences (Q2044479) (← links)
• Accelerated Bregman proximal gradient methods for relatively smooth convex optimization (Q2044481) (← links)
• A Laplacian approach to \(\ell_1\)-norm minimization (Q2044482) (← links)
• A FISTA-type accelerated gradient algorithm for solving smooth nonconvex composite optimization problems (Q2044494) (← links)
• Sparse group fused Lasso for model segmentation: a hybrid approach (Q2051576) (← links)
• A fast and efficient smoothing approach to Lasso regression and an application in statistical genetics: polygenic risk scores for chronic obstructive pulmonary disease (COPD) (Q2058755) (← links)
• An inexact proximal augmented Lagrangian framework with arbitrary linearly convergent inner solver for composite convex optimization (Q2062324) (← links)
• Superquantiles at work: machine learning applications and efficient subgradient computation (Q2070410) (← links)
• Learning subtree pattern importance for Weisfeiler-Lehman based graph kernels (Q2071309) (← links)
• Discrete conditional-expectation-based simulation optimization: methodology and applications (Q2076929) (← links)
• Parallel subgradient algorithm with block dual decomposition for large-scale optimization (Q2077960) (← links)
• Generalized Nesterov's accelerated proximal gradient algorithms with convergence rate of order \(o(1/k^2)\) (Q2082553) (← links)
• Finding extremals of Lagrangian actions (Q2094445) (← links)
• A stochastic Nesterov's smoothing accelerated method for general nonsmooth constrained stochastic composite convex optimization (Q2103421) (← links)
• Extrapolated smoothing descent algorithm for constrained nonconvex and nonsmooth composite problems (Q2105897) (← links)
• Network manipulation algorithm based on inexact alternating minimization (Q2109010) (← links)
• On stochastic accelerated gradient with convergence rate (Q2111814) (← links)