4 papers
Modified Bryson-Frazier Smoothing and Hyperparameter Learning for Temporal Gaussian Process Regression
Tom Colemont, Brecht Evens, Tjonnie G. F. Li +1
One-dimensional Gaussian processes with stationary, integrable kernel functions admit exact or arbitrarily accurate state-space representations, enabling linear-time inference thro…
Scaled Relative Graphs for Nonmonotone Operators with Applications in Circuit Theory
Jan Quan, Brecht Evens, Rodolphe Sepulchre +1
The scaled relative graph (SRG) is a powerful graphical tool for analyzing the properties of operators, by mapping their graph onto the complex plane. In this work, we study the SR…
Spingarn's Method and Progressive Decoupling Beyond Elicitable Monotonicity
Brecht Evens, Puya Latafat, Panagiotis Patrinos
Spingarn's method of partial inverses and the progressive decoupling algorithm address inclusion problems involving the sum of an operator and the normal cone of a linear subspace,…
Convergence of the Chambolle-Pock Algorithm in the Absence of Monotonicity
Brecht Evens, Puya Latafat, Panagiotis Patrinos
The Chambolle-Pock algorithm (CPA), also known as the primal-dual hybrid gradient method, has gained popularity over the last decade due to its success in solving large-scale conve…