Publications related to Linear programming

Optimization methods and objective functions for analysis of metabolic network models

Computational studies of metabolism aim to systematically analyze the metabolic behaviour of biological systems in different conditions. Genome-scale metabolic network models (GEMs) capture the connection between elements of the network by applying stoichi ...

EPFL2020

CPGD: Cadzow Plug-and-Play Gradient Descent for Generalised FRI

Martin Vetterli, Paul Hurley, Matthieu Martin Jean-André Simeoni, Adrien Georges Jean Besson

Finite rate of innovation (FRI) is a powerful reconstruction framework enabling the recovery of sparse Dirac streams from uniform low-pass filtered samples. An extension of this framework, called generalised FRI (genFRI), has been recently proposed for han ...

2020

A Catalyst Framework for Minimax Optimization

Negar Kiyavash

We introduce a generic \emph{two-loop} scheme for smooth minimax optimization with strongly-convex-concave objectives. Our approach applies the accelerated proximal point framework (or Catalyst) to the associated \emph{dual problem} and takes full advantag ...

2020

Optimum design of frame structures from a stock of reclaimed elements

Corentin Jean Dominique Fivet, Gennaro Senatore, Jan Friedrich Georg Brütting

This paper presents optimization methods to design frame structures from a stock of existing elements. These methods are relevant when reusing structural elements over multiple service lives. Reuse has the potential to reduce the environmental impact of bu ...

2020

Feedback Control Design Maximizing the Region of Attraction of Stochastic Systems Using Polynomial Chaos Expansion

Petr Listov

A feedback control design is proposed for stochastic systems with finite second moment which aims at maximising the region of attraction of the equilibrium point. Polynomial Chaos (PC) expansions are employed to represent the stochastic closed loop system ...

2020

Stationary Structures near the Kolmogorov and Poiseuille Flows in the 2d Euler Equations

Klaus Martin Widmayer

We study the behavior of solutions to the incompressible 2d Euler equations near two canonical shear flows with critical points, the Kolmogorov and Poiseuille flows, with consequences for the associated Navier-Stokes problems. We exhibit a large family of ...

2020

On the Complexity of Modulo-q Arguments and the Chevalley - Warning Theorem

Mika Tapani Göös

We study the search problem class PPA_q defined as a modulo-q analog of the well-known polynomial parity argument class PPA introduced by Papadimitriou (JCSS 1994). Our first result shows that this class can be characterized in terms of PPA_p for prime p. ...

Schloss Dagstuhl - Leibniz-Zentrum für Informatik2020

Linear convergence of primal-dual gradient methods and their performance in distributed optimization

Ali H. Sayed, Sulaiman A S A E Alghunaim

In this work, we revisit a classical incremental implementation of the primal-descent dual-ascent gradient method used for the solution of equality constrained optimization problems. We provide a short proof that establishes the linear (exponential) conver ...

PERGAMON-ELSEVIER SCIENCE LTD2020

New Results in Integer and Lattice Programming

Christoph Hunkenschröder

An integer program (IP) is a problem of the form

\min \{f(x) : \, Ax = b, \ l \leq x \leq u, \ x \in \Z^n\}

, where

A \in \Z^{m \times n}

,

b \in \Z^m

,

l,u \in \Z^n

, and

f: \Z^n \rightarrow \Z

is a separable convex objective function. The problem o ...

EPFL2020

First Order Methods For Globally Optimal Distributed Controllers Beyond Quadratic Invariance

Maryam Kamgarpour, Luca Furieri

We study the distributed Linear Quadratic Gaussian (LQG) control problem in discrete-time and finite-horizon, where the controller depends linearly on the history of the outputs and it is required to lie in a given subspace, e.g. to possess a certain spars ...

IEEE2020

Linear programming

Graph Chatbot

Chat with Graph Search

Optimization methods and objective functions for analysis of metabolic network models

CPGD: Cadzow Plug-and-Play Gradient Descent for Generalised FRI

A Catalyst Framework for Minimax Optimization

Optimum design of frame structures from a stock of reclaimed elements

Feedback Control Design Maximizing the Region of Attraction of Stochastic Systems Using Polynomial Chaos Expansion

Stationary Structures near the Kolmogorov and Poiseuille Flows in the 2d Euler Equations

On the Complexity of Modulo-q Arguments and the Chevalley - Warning Theorem

Linear convergence of primal-dual gradient methods and their performance in distributed optimization

New Results in Integer and Lattice Programming

First Order Methods For Globally Optimal Distributed Controllers Beyond Quadratic Invariance

CPGD: Cadzow Plug-and-Play Gradient Descent for Generalised FRI

Optimization methods and objective functions for analysis of metabolic network models

Optimum design of frame structures from a stock of reclaimed elements

A Catalyst Framework for Minimax Optimization

Feedback Control Design Maximizing the Region of Attraction of Stochastic Systems Using Polynomial Chaos Expansion

Stationary Structures near the Kolmogorov and Poiseuille Flows in the 2d Euler Equations

On the Complexity of Modulo-q Arguments and the Chevalley - Warning Theorem

Linear convergence of primal-dual gradient methods and their performance in distributed optimization

New Results in Integer and Lattice Programming

First Order Methods For Globally Optimal Distributed Controllers Beyond Quadratic Invariance