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Complexity Certification of the Fast Alternating Minimization Algorithm for Linear Model Predictive Control

Publications associées (36)

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Complexity Certification of the Fast Alternating Minimization Algorithm for Linear MPC

Colin Neil Jones, Ye Pu, Melanie Nicole Zeilinger

In this technical note, the fast alternating minimization algorithm (FAMA) is proposed to solve model predictive control (MPC) problems with polytopic and second-order cone constraints. Two splitting strategies with efficient implementations for MPC proble ...

2017

LPN in Cryptography

Sonia Mihaela Bogos

The security of public-key cryptography relies on well-studied hard problems, problems for which we do not have efficient algorithms. Factorization and discrete logarithm are the two most known and used hard problems. Unfortunately, they can be easily solv ...

EPFL2017

On Generalized Primal-Dual Interior-Point Methods with Non-uniform Complementarity Perturbations for Quadratic Programming

Colin Neil Jones, Altug Bitlislioglu

This technical note discusses convergence conditions of a generalized variant of primal-dual interior point methods. The generalization arises due to the permitted case of having a non-uniform complementarity perturbation vector, which is equivalent to hav ...

2017

Splitting Methods for Distributed Optimization and Control

Ye Pu

This thesis contributes towards the design and analysis of fast and distributed optimization algorithms based on splitting techniques, such as proximal gradient methods or alternation minimization algorithms, with the application of solving model predictiv ...

EPFL2016

Fast Robust PCA on Graphs

Pierre Vandergheynst, Gilles Puy, Nathanaël Perraudin, Nauman Shahid, Vasilis Kalofolias

Mining useful clusters from high dimensional data has received significant attention of the computer vision and pattern recognition community in the recent years. Linear and non-linear dimensionality reduction has played an important role to overcome the c ...

Ieee-Inst Electrical Electronics Engineers Inc2016

A Primal-dual Framework For Mixtures Of Regularisers

Volkan Cevher, Cosimo Aprile, Quoc Tran Dinh, Luca Baldassarre, Baran Gözcü

Effectively solving many inverse problems in engineering requires to leverage all possible prior information about the structure of the signal to be estimated. This often leads to tackling constrained optimization problems with mixtures of regularizers. Pr ...

2015

Tight Bounds for Asynchronous Renaming

Rachid Guerraoui, Seth Gilbert, Dan Alistarh

This article presents the first tight bounds on the time complexity of shared-memory renaming, a fundamental problem in distributed computing in which a set of processes need to pick distinct identifiers from a small namespace. We first prove an individual ...

Association for Computing Machinery2014

Low-rank tensor completion by Riemannian optimization

Daniel Kressner, Michael Maximilian Steinlechner

In tensor completion, the goal is to fill in missing entries of a partially known tensor under a low-rank constraint. We propose a new algorithm that performs Riemannian optimization techniques on the manifold of tensors of fixed multilinear rank. More spe ...

Springer2014

FETI-DP Domain Decomposition Method

Christoph Jäggli

FETI-DP is a dual iterative, nonoverlapping domain decomposition method. By a Schur complement procedure, the solution of a boundary value problem is reduced to solving a symmetric and positive definite dual problem in which the variables are directly rela ...

2014

Fast Byzantine Agreement

Rachid Guerraoui, Florian Huc

This paper presents the first probabilistic Byzantine Agreement algorithm whose communication and time complexities are poly-logarithmic. So far, the most effective probabilistic Byzantine Agreement algorithm had communication complexity and time complexit ...

2013