Pages that link to "Item:Q122993"

The following pages link to Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers (Q122993):

Displaying 50 items.

• Monotone splitting sequential quadratic optimization algorithm with applications in electric power systems (Q779870) (← links)
• New robust principal component analysis for joint image alignment and recovery via affine transformations, Frobenius and \(L_{2,1}\) norms (Q779978) (← links)
• Scalable Gaussian kernel support vector machines with sublinear training time complexity (Q780936) (← links)
• Twist tensor total variation regularized-reweighted nuclear norm based tensor completion for video missing area recovery (Q781059) (← links)
• Generalized ADMM with optimal indefinite proximal term for linearly constrained convex optimization (Q781096) (← links)
• Distributed block-diagonal approximation methods for regularized empirical risk minimization (Q782443) (← links)
• Convergence study of indefinite proximal ADMM with a relaxation factor (Q782911) (← links)
• Key-frame detection and super-resolution of hyperspectral video via sparse-based cumulative tensor factorization (Q783190) (← links)
• Ellipse fitting via low-rank generalized multidimensional scaling matrix recovery (Q784511) (← links)
• Managing randomization in the multi-block alternating direction method of multipliers for quadratic optimization (Q823888) (← links)
• Low-rank registration of images captured under unknown, varying lighting (Q826157) (← links)
• Local R-linear convergence of ADMM-based algorithm for \(\ell_1\)-norm minimization with linear and box constraints (Q826824) (← links)
• Alternating direction method of multipliers with variable metric indefinite proximal terms for convex optimization (Q827573) (← links)
• A self-calibrated direct approach to precision matrix estimation and linear discriminant analysis in high dimensions (Q829737) (← links)
• An adapted linear discriminant analysis with variable selection for the classification in high-dimension, and an application to medical data (Q830539) (← links)
• Hybrid safe-strong rules for efficient optimization in Lasso-type problems (Q830584) (← links)
• Linearized symmetric multi-block ADMM with indefinite proximal regularization and optimal proximal parameter (Q831269) (← links)
• A fast splitting method tailored for Dantzig selector (Q887167) (← links)
• Inexact accelerated augmented Lagrangian methods (Q887168) (← links)
• Quadratic kernel-free least squares support vector machine for target diseases classification (Q887869) (← links)
• On the sublinear convergence rate of multi-block ADMM (Q888303) (← links)
• An iterative SVM approach to feature selection and classification in high-dimensional datasets (Q888553) (← links)
• An inertial forward-backward algorithm for monotone inclusions (Q890044) (← links)
• Numerical methods for parameter estimation in Poisson data inversion (Q890095) (← links)
• A proximal alternating linearization method for minimizing the sum of two convex functions (Q892779) (← links)
• Distributed estimation of Laplacian eigenvalues via constrained consensus optimization problems (Q893994) (← links)
• Guaranteed recovery of planted cliques and dense subgraphs by convex relaxation (Q896191) (← links)
• Compositional performance certification of interconnected systems using ADMM (Q900650) (← links)
• Metric selection in fast dual forward-backward splitting (Q901087) (← links)
• P-splines with an \(\ell_1\) penalty for repeated measures (Q1616325) (← links)
• Group subset selection for linear regression (Q1623472) (← links)
• Linearized alternating direction method of multipliers for sparse group and fused Lasso models (Q1623671) (← links)
• Stochastic accelerated alternating direction method of multipliers with importance sampling (Q1626518) (← links)
• Distributed stochastic algorithm for global optimization in networked system (Q1626540) (← links)
• Nash equilibrium seeking for \(N\)-coalition noncooperative games (Q1626894) (← links)
• A fixed-time convergent algorithm for distributed convex optimization in multi-agent systems (Q1626951) (← links)
• Image colorization based on a generalization of the low dimensional manifold model (Q1632202) (← links)
• An alternating direction method of multipliers for MCP-penalized regression with high-dimensional data (Q1633879) (← links)
• The combination projection method for solving convex feasibility problems (Q1634718) (← links)
• Solving uncalibrated photometric stereo using fewer images by jointly optimizing low-rank matrix completion and integrability (Q1635999) (← links)
• Variational methods for normal integration (Q1636005) (← links)
• A deconvolution path for mixtures (Q1639196) (← links)
• A nonconvex formulation for low rank subspace clustering: algorithms and convergence analysis (Q1639712) (← links)
• 1-bit matrix completion: PAC-Bayesian analysis of a variational approximation (Q1640399) (← links)
• Consensus-based modeling using distributed feature construction with ILP (Q1640573) (← links)
• Is ADMM always faster than average consensus? (Q1641079) (← links)
• Power-imbalance allocation control of power systems-secondary frequency control (Q1642202) (← links)
• A decomposable self-adaptive projection-based prediction-correction algorithm for convex time space network flow problem (Q1644557) (← links)
• A simplified view of first order methods for optimization (Q1650767) (← links)
• Optimal distributed task scheduling in volunteer clouds (Q1652245) (← links)