• # IR Tools

• Referenced in 49 articles [sw26721]
• Tools: A MATLAB Package of Iterative Regularization Methods and Large-Scale Test Problems. This paper ... MATLAB software package of iterative regularization methods and test problems for large-scale linear inverse ... linear inverse problems. The solvers include iterative regularization methods where the regularization ... iterative methods requires only this matrix and the right hand side vector; if the method...
• # softImpute

• Referenced in 74 articles [sw12263]
• Thresholded SVD. Iterative methods for matrix completion that use nuclear-norm regularization. There ... main approaches.The one approach uses iterative soft-thresholded svds to impute the missing values...
• # AIR tools

• Referenced in 92 articles [sw09203]
• iterative reconstruction (AIR) methods for discretizations of inverse problems. These so-called row action methods ... achieving the necessary regularization of the problem. Two classes of methods are implemented: Algebraic reconstruction ... techniques and simultaneous iterative reconstruction techniques. In addition we provide a few simplified test problems...
• # TIGRA

• Referenced in 40 articles [sw02333]
• TIGRA -- an iterative algorithm for regularizing nonlinear ill-posed problems. A sophisticated numerical analysis ... combination of Tikhonov regularization and the gradient method for solving nonlinear ill-posed problems ... TIGRA (Tikhonov-gradient method) algorithm proposed uses steepest descent iterations in an inner loop ... solutions with a fixed regularization parameter and a parameter iteration for satisfying a discrepancy criterion...
• # Pegasos

• Referenced in 103 articles [sw08752]
• stochastic gradient descent methods for SVMs require Ω(1/ϵ2) iterations. As in previously devised ... iterations also scales linearly with 1/λ, where λ is the regularization parameter ... kernel, the total run-time of our method is O (d/(λϵ)) , where...

• Referenced in 157 articles [sw22202]
• methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations ... risk minimization problems with common and important regularization functions and domain constraints. We experimentally study ... theoretical analysis and show that adaptive subgradient methods outperform state...
• # BayesTree

• Referenced in 64 articles [sw07995]
• BayesTree: Bayesian Methods for Tree Based Models: Implementation of BART: Bayesian Additive Regression Trees ... where each tree is constrained by a regularization prior to be a weak learner ... fitting and inference are accomplished via an iterative Bayesian backfitting MCMC algorithm that generates samples ... adaptive random basis elements. Motivated by ensemble methods in general, and boosting algorithms in particular...
• # BartPy

• Referenced in 83 articles [sw40584]
• where each tree is constrained by a regularization prior to be a weak learner ... fitting and inference are accomplished via an iterative Bayesian backfitting MCMC algorithm that generates samples ... adaptive random basis elements. Motivated by ensemble methods in general, and boosting algorithms in particular...
• # HyBR

• Referenced in 7 articles [sw29132]
• decreases. Hybrid methods apply a standard regularization technique, such as Tikhonov regularization ... projected problem at each iteration. Thus, regularization in hybrid methods is achieved both by Krylov ... choice of a regularization parameter at each iteration...
• # FPC_AS

• Referenced in 68 articles [sw12218]
• fast algorithm for solving the ℓ 1 -regularized minimization problem ... first stage a first-order iterative “shrinkage” method yields an estimate of the subset...
• # SLEP

• Referenced in 41 articles [sw13487]
• Features: 1) First-Order Method. At each iteration, we only need to evaluate the function ... optimization via the first-order black-box methods. 3) Efficient Projection. The projection problem (proximal ... pathwise solutions corresponding to a series of regularization parameters by the “warm-start” technique...
• # SpaRSA

• Referenced in 3 articles [sw20467]
• nonsmooth, possibly nonconvex regular izer. We propose iterative methods in which each step is obtained ... unknowns) plus the original sparsity-inducing regularizer; our approach is suitable for cases in which ... convexity of the regularizer), we prove convergence of the proposed iterative algorithm to a minimum ... other regularizers, such as an 1-norm and group-separable regularizers. It also generalizes immediately...
• # bilevel

• Referenced in 5 articles [sw25305]
• propose a method that first solves iteratively a set of regularized MPCCs using ... shelf mixed-integer solvers. This method is tested using a wide range of randomly generated...
• # LSTRS

• Referenced in 32 articles [sw04729]
• region subproblems and regularization A MATLAB 6.0 implementation of the LSTRS method is presented. LSTRS ... quadratic problems with one norm constraint. The method is based on a reformulation ... parameterized eigenvalue problem, and consists of an iterative procedure that finds the optimal value...
• # ParNes

• Referenced in 12 articles [sw08366]