scientific article
From MaRDI portal
Publication:3174129
zbMath1222.62092MaRDI QIDQ3174129
Kwangmoo Koh, Seung-Jean Kim, Stephen P. Boyd
Publication date: 12 October 2011
Full work available at URL: http://jmlr.csail.mit.edu/papers/v8/koh07a.html
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Related Items
A Trust-region Method for Nonsmooth Nonconvex Optimization, A regularized interior-point method for constrained linear least squares, Optimality conditions for sparse nonlinear programming, Estimation of dynamic systems using a method of characteristics filter, Alternating direction method of multipliers with variable metric indefinite proximal terms for convex optimization, Feature subset selection for logistic regression via mixed integer optimization, Sequence-based prediction of protein-protein interaction sites with L1-logreg classifier, Parameter choices for sparse regularization with the ℓ1 norm *, Block coordinate proximal gradient methods with variable Bregman functions for nonsmooth separable optimization, Copula density estimation by finite mixture of parametric copula densities, Smoothing strategy along with conjugate gradient algorithm for signal reconstruction, JANOS: An Integrated Predictive and Prescriptive Modeling Framework, A proximal ADMM with the Broyden family for convex optimization problems, Space alternating penalized Kullback proximal point algorithms for maximizing likelihood with nondifferentiable penalty, Restricted Robinson constraint qualification and optimality for cardinality-constrained cone programming, A smoothing neural network for minimization \(l_1\)-\(l_p\) in sparse signal reconstruction with measurement noises, Building up a robust risk mathematical platform to predict colorectal cancer, Recovering occlusion boundaries from an image, An inexact proximal generalized alternating direction method of multipliers, Gene selection and prediction for cancer classification using support vector machines with a reject option, Coordinate ascent for penalized semiparametric regression on high-dimensional panel count data, Dimension reduction and variable selection in case control studies via regularized likelihood optimization, Kernel logistic regression using truncated Newton method, Iterative reweighted minimization methods for \(l_p\) regularized unconstrained nonlinear programming, Multinomial regression with elastic net penalty and its grouping effect in gene selection, Nonmonotone Barzilai-Borwein gradient algorithm for \(\ell_1\)-regularized nonsmooth minimization in compressive sensing, Spatial general autoregressive model-based image interpolation accommodates arbitrary scale factors, A relaxed interior point method for low-rank semidefinite programming problems with applications to matrix completion, Inexact primal–dual gradient projection methods for nonlinear optimization on convex set, MLSLR: multilabel learning via sparse logistic regression, A pseudo-heuristic parameter selection rule for \(l^1\)-regularized minimization problems, ADMM-softmax: an ADMM approach for multinomial logistic regression, Support vector machines based on convex risk functions and general norms, Logistic regression: from art to science, Sparse optimization in feature selection: application in neuroimaging, Incrementally updated gradient methods for constrained and regularized optimization, Empirical comparison study of approximate methods for structure selection in binary graphical models, A coordinate gradient descent method for \(\ell_{1}\)-regularized convex minimization, High-dimensional Ising model selection using \(\ell _{1}\)-regularized logistic regression, Estimating time-varying networks, Dimensionality reduction for density ratio estimation in high-dimensional spaces, Recovery of seismic wavefields by an \(l_{q}\)-norm constrained regularization method, Inexact proximal memoryless quasi-Newton methods based on the Broyden family for minimizing composite functions, Globalized inexact proximal Newton-type methods for nonconvex composite functions, An extended Newton-type algorithm for \(\ell_2\)-regularized sparse logistic regression and its efficiency for classifying large-scale datasets, On the Complexity of Logistic Regression Models, APPLE: approximate path for penalized likelihood estimators, Another look at linear programming for feature selection via methods of regularization, Large‐scale regression‐based pattern discovery: The example of screening the WHO global drug safety database, SMT: Sparse multivariate tree, Sparse Recovery via Partial Regularization: Models, Theory, and Algorithms, A linearly convergent algorithm without prior knowledge of operator norms for solving \(\ell_1 - \ell_2\) minimization, A Multilevel Framework for Sparse Optimization with Application to Inverse Covariance Estimation and Logistic Regression, A partially inexact proximal alternating direction method of multipliers and its iteration-complexity analysis, Gap Safe screening rules for sparsity enforcing penalties, Nonmonotone Enhanced Proximal DC Algorithms for a Class of Structured Nonsmooth DC Programming, Weighted thresholding homotopy method for sparsity constrained optimization, On the local convergence of a stochastic semismooth Newton method for nonsmooth nonconvex optimization, Optimizing optimization: accurate detection of hidden interactions in active body systems from noisy data, Unnamed Item, Mixed linear system estimation and identification, A Lagrange-Newton algorithm for sparse nonlinear programming