1 citations · 2 across the 5 of their papers we have counts for
5 papers
GPU-Accelerated Sequential Quadratic Programming Algorithm for Solving ACOPF
Bowen Li, Michel Schanen, Kibaek Kim
Sequential quadratic programming (SQP) is widely used in solving nonlinear optimization problem, with advantages of warm-starting solutions, as well as finding high-accurate soluti…
Parallel Interior-Point Solver for Block-Structured Nonlinear Programs on SIMD/GPU Architectures
François Pacaud, Michel Schanen, Sungho Shin +2
We investigate how to port the standard interior-point method to new exascale architectures for block-structured nonlinear programs with state equations. Computationally, we decomp…
On automatic differentiation for the Matérn covariance
Oana Marin, Christopher Geoga, Michel Schanen
To target challenges in differentiable optimization we analyze and propose strategies for derivatives of the Matérn kernel with respect to the smoothness parameter. This problem is…
Fitting Matérn Smoothness Parameters Using Automatic Differentiation
Christopher J. Geoga, Oana Marin, Michel Schanen +1
The Matérn covariance function is ubiquitous in the application of Gaussian processes to spatial statistics and beyond. Perhaps the most important reason for this is that the smoot…
A Globally Convergent Distributed Jacobi Scheme for Block-Structured Nonconvex Constrained Optimization Problems
Anirudh Subramanyam, Youngdae Kim, Michel Schanen +2
Motivated by the increasing availability of high-performance parallel computing, we design a distributed parallel algorithm for linearly-coupled block-structured nonconvex constrai…