Found 1874 results, showing the newest relevant preprints. Sort by relevancy only.Update me on new preprints

A Trust-Region Method For Nonsmooth Nonconvex Optimization

We propose a trust-region type method for general nonsmooth nonconvex optimization problems with emphasis on nonsmooth composite programs where the objective function is a summation of a (probably nonconvex) smooth function and a (probably nonsmooth) convex function. Expand abstract.
5 days ago
5/10 relevant
arXiv

Multiplicative Noise Removal: Nonlocal Low-Rank Model and Its Proximal Alternating Reweighted Minimization Algorithm

To solve this optimization problem, we propose the PARM algorithm, which has a proximal alternating scheme with a reweighted approximation of its subproblem. Expand abstract.
6 days ago
4/10 relevant
arXiv

Estimating processes in adapted Wasserstein distance

Specifically, the adapted Wasserstein distance allows to control the error in stochastic optimization problems, pricing and hedging problems, optimal stopping problems, etc. in a Lipschitz fashion. Expand abstract.
7 days ago
4/10 relevant
arXiv

Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization

We develop two new stochastic Gauss-Newton algorithms for solving a class of stochastic nonconvex compositional optimization problems frequently arising in practice. Expand abstract.
7 days ago
4/10 relevant
arXiv

On Generalization and Acceleration of Randomized Projection Methods for Linear Feasibility Problems

Randomized Kaczmarz (RK), Motzkin Method (MM) and Sampling Kaczmarz Motzkin (SKM) algorithms are commonly used iterative techniques for solving linear system of inequalities (i.e., $Ax \leq b$). Expand abstract.
7 days ago
4/10 relevant
arXiv

Convex Optimization on Functionals of Probability Densities

In information theory, some optimization problems result in convex optimization problems on strictly convex functionals of probability densities. Expand abstract.
9 days ago
5/10 relevant
arXiv

Explicit Multi-objective Model Predictive Control for Nonlinear Systems Under Uncertainty

Furthermore, in order to ensure optimality of the solutions, we include an additional online optimization step, which is considerably cheaper than the original multi-objective optimization problem. Expand abstract.
10 days ago
4/10 relevant
arXiv

Model Reduction Framework with a New Take on Active Subspaces for Optimization Problems with Linearized Fluid-Structure Interaction Constraints

The obtained results illustrate the feasibility of the computational framework for realistic MDAO problems and highlight the benefits of the new approach for constructing an active subspace in both terms of solution optimality and wall-clock time reduction Expand abstract.
11 days ago
8/10 relevant
arXiv

Two-Stage Adjustable Robust Linear Optimization with New Quadratic Decision Rules: Exact SDP Reformulations

We then show via numerical experiments on lot-sizing problems with uncertain demand that adjustable robust linear optimization problems with QDRs improve upon the affine decision rules in their performance both in the worst-case sense and after simulated realization of the uncertain demand relative... Expand abstract.
12 days ago
6/10 relevant
arXiv

Stochastic Online Optimization using Kalman Recursion

The EKF appears as a parameter-free O(d^2) online algorithm that optimally solves some unconstrained optimization problems. Expand abstract.
14 days ago
4/10 relevant
arXiv