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Bilevel optimization problems embed the optimality of a subproblem as a constraint of another optimization problem. We introduce the concept of near-optimality robustness for bilevel optimization, protecting the upper-level solution…

Optimization and Control · Mathematics 2024-07-15 Mathieu Besançon , Miguel F. Anjos , Luce Brotcorne

The complexity-performance trade-off is a fundamental aspect of the design of low-density parity-check (LDPC) codes. In this paper, we consider LDPC codes for the binary erasure channel (BEC), use code rate for performance metric, and…

Information Theory · Computer Science 2016-11-17 Vahid Jamali , Yasser Karimian , Johannes Huber , Mahmoud Ahmadian

It is well known that bilevel optimization problems are hard to solve both in theory and practice. In this paper, we highlight a further computational difficulty when it comes to solving bilevel problems with continuous but nonconvex lower…

Optimization and Control · Mathematics 2023-05-04 Yasmine Beck , Daniel Bienstock , Martin Schmidt , Johannes Thürauf

We propose a general algorithm to enumerate all solutions of a zero-dimensional polynomial system with respect to a given cost function. The algorithm is developed and is used to study a polynomial system obtained by discretizing the steady…

Numerical Analysis · Mathematics 2008-11-17 Martin Mevissen , Kosuke Yokoyama , Nobuki Takayama

We consider the robust version of a multi-commodity network flow problem. The robustness is defined with respect to the deletion, or failure, of edges. While the flow problem itself is a polynomially-sized linear program, its robust version…

Optimization and Control · Mathematics 2025-04-25 Artyom Klyuchikov , Roland Hildebrand , Sergei Protasov , Alexander Rogozin , Alexei Chernov

The numerical simulation of large-scale multiphase flow in porous media is of considerable importance across various application fields, particularly in the petroleum industry. The fully implicit method is preferred in reservoir simulations…

Numerical Analysis · Mathematics 2026-04-13 Shizhe Li , Li Zhao , Chen-Song Zhang

In the current industry, the development of optimized mechanical components able to satisfy the customer requirements evolves quickly. Therefore, companies are asked for efficient solutions to improve their products in terms of stiffness…

Computational Engineering, Finance, and Science · Computer Science 2023-07-31 Rafael Merli , Antolín Martínez-Martínez , Juan José Ródenas , Marc Bosch-Galera , Enrique Nadal

We discuss here the application of the simultaneous block diagonalization (SBD) of matrices to the study of the stability of both complete and cluster synchronization in random (generic) networks. For both problems, we define indices that…

Disordered Systems and Neural Networks · Physics 2022-02-02 Shirin Panahi , Nelson Amaya , Isaac Klickstein , Galen Novello , Francesco Sorrentino

We consider the coupled system of equations that describe flow in fractured porous media. To describe such types of problems, multicontinuum and multiscale approaches are used. Because in multicontinuum models, the permeability of each…

Numerical Analysis · Mathematics 2023-05-31 Maria Vasilyeva

In this paper we propose a novel parallel stochastic coordinate descent (SCD) algorithm with convergence guarantees that exhibits strong scalability. We start by studying a state-of-the-art parallel implementation of SCD and identify…

Machine Learning · Computer Science 2019-11-19 Nikolas Ioannou , Celestine Mendler-Dünner , Thomas Parnell

In this paper we present a topology optimization technique applicable to a broad range of flow design problems. We propose also a discrete adjoint formulation effective for a wide class of Lattice Boltzmann Methods (LBM). This adjoint…

Computational Engineering, Finance, and Science · Computer Science 2015-01-21 Łukasz Łaniewski-Wołłk , Jacek Rokicki

We propose and analyze a block coordinate descent proximal algorithm (BCD-prox) for simultaneous filtering and parameter estimation of ODE models. As we show on ODE systems with up to d=40 dimensions, as compared to state-of-the-art…

Machine Learning · Computer Science 2019-05-28 Ramin Raziperchikolaei , Harish S. Bhat

This work proposes a method for solving linear stochastic optimal control (SOC) problems using sum of squares and semidefinite programming. Previous work had used polynomial optimization to approximate the value function, requiring a high…

Optimization and Control · Mathematics 2014-09-23 Matanya B. Horowitz , Ivan Papusha , Joel W. Burdick

The aim of this work is to present a parallel solver for a formulation of fluid-structure interaction (FSI) problems which makes use of a distributed Lagrange multiplier in the spirit of the fictitious domain method. The fluid subproblem,…

Numerical Analysis · Mathematics 2025-03-28 Daniele Boffi , Fabio Credali , Lucia Gastaldi , Simone Scacchi

Multistage stochastic optimization problems are, by essence, complex as their solutions are indexed both by stages and by uncertainties. Their large scale nature makes decomposition methods appealing, like dynamic programming which is a…

Optimization and Control · Mathematics 2023-05-01 Pierre Carpentier , Jean-Philippe Chancelier , Michel de Lara , Thomas Martin , Tristan Rigaut

We consider a three-level parallelisation scheme. The second and third levels define a classical two-level parallelisation scheme and some load balancing algorithm is used to distribute tasks among processes. It is well-known that for many…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-09-24 Rima Kriauzienė , Andrej Bugajev , Raimondas Čiegis

We introduce a generalization of the linearized Alternating Direction Method of Multipliers to optimize a real-valued function $f$ of multiple arguments with potentially multiple constraints $g_\circ$ on each of them. The function $f$ may…

Optimization and Control · Mathematics 2019-01-28 Fred Moolekamp , Peter Melchior

Multiscale analysis of a degenerate pseudoparabolic variational inequality, modelling the two-phase flow with dynamical capillary pressure in a perforated domain, is the main topic of this work. Regularisation and penalty operator methods…

Analysis of PDEs · Mathematics 2018-10-01 Mariya Ptashnyk

Stochastic Dual Coordinate Descent (SDCD) has become one of the most efficient ways to solve the family of $\ell_2$-regularized empirical risk minimization problems, including linear SVM, logistic regression, and many others. The vanilla…

Machine Learning · Computer Science 2015-04-07 Cho-Jui Hsieh , Hsiang-Fu Yu , Inderjit S. Dhillon

We consider two-level finite element discretization methods for the stream function formulation of the Navier-Stokes equations. The two-level method consists of solving a small nonlinear system on the coarse mesh, then solving a linear…

Numerical Analysis · Mathematics 2025-10-20 Faisal Fairag
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