no code implementations • 30 Jun 2023 • Idris Kempf, Paul Goulart, Stephen Duncan
We show that our proposed approximations can yield stable systems even when the Frobenius norm approximation does not.
no code implementations • 20 Nov 2022 • Steffen Ridderbusch, Sina Ober-Blöbaum, Paul Goulart
Computing the distribution of trajectories from a Gaussian Process model of a dynamical system is an important challenge in utilizing such models.
1 code implementation • 10 Nov 2020 • Steffen Ridderbusch, Christian Offen, Sina Ober-Blöbaum, Paul Goulart
Recent advances in learning techniques have enabled the modelling of dynamical systems for scientific and engineering applications directly from data.
2 code implementations • 30 Jan 2019 • Michael Garstka, Mark Cannon, Paul Goulart
This paper describes the Conic Operator Splitting Method (COSMO) solver, an operator splitting algorithm for convex optimisation problems with quadratic objective function and conic constraints.
Optimization and Control
2 code implementations • 21 Nov 2017 • Bartolomeo Stellato, Goran Banjac, Paul Goulart, Alberto Bemporad, Stephen Boyd
We present a general purpose solver for convex quadratic programs based on the alternating direction method of multipliers, employing a novel operator splitting technique that requires the solution of a quasi-definite linear system with the same coefficient matrix at almost every iteration.
Optimization and Control
2 code implementations • 17 Jul 2017 • Yang Zheng, Giovanni Fantuzzi, Antonis Papachristodoulou, Paul Goulart, Andrew Wynn
We employ chordal decomposition to reformulate a large and sparse semidefinite program (SDP), either in primal or dual standard form, into an equivalent SDP with smaller positive semidefinite (PSD) constraints.
Optimization and Control
2 code implementations • 6 Nov 2016 • Yang Zheng, Giovanni Fantuzzi, Antonis Papachristodoulou, Paul Goulart, Andrew Wynn
We propose an efficient first-order method, based on the alternating direction method of multipliers (ADMM), to solve the homogeneous self-dual embedding problem for a primal-dual pair of semidefinite programs (SDPs) with chordal sparsity.
Optimization and Control
2 code implementations • 20 Sep 2016 • Yang Zheng, Giovanni Fantuzzi, Antonis Papachristodoulou, Paul Goulart, Andrew Wynn
We show that chordal decomposition can be applied to either the primal or the dual standard form of a sparse SDP, resulting in scaled versions of ADMM algorithms with the same computational cost.
Optimization and Control