2 citations · 5 across the 9 of their papers we have counts for
4 papers · 1 filter
Asynchronous Nonlinear Sheaf Diffusion for Multi-Agent Coordination
Yichen Zhao, Tyler Hanks, Hans Riess +3
Cellular sheaves and sheaf Laplacians provide a far-reaching generalization of graphs and graph Laplacians, resulting in a wide array of applications ranging from machine learning…
Distributed Multi-agent Coordination over Cellular Sheaves
Tyler Hanks, Hans Riess, Samuel Cohen +3
Techniques for coordination of multi-agent systems are vast and varied, often utilizing purpose-built solvers or controllers with tight coupling to the types of systems involved or…
A Compositional Framework for First-Order Optimization
Tyler Hanks, Matthew Klawonn, Evan Patterson +2
Optimization decomposition methods are a fundamental tool to develop distributed solution algorithms for large scale optimization problems arising in fields such as machine learnin…
Modeling Model Predictive Control: A Category Theoretic Framework for Multistage Control Problems
Tyler Hanks, Baike She, Matthew Hale +3
Model predictive control (MPC) is an optimal control technique which involves solving a sequence of constrained optimization problems across a given time horizon. In this paper, we…