3 citations · 4 across the 7 of their papers we have counts for
4 papers · 1 filter
Technical Report: A Totally Asynchronous Nesterov's Accelerated Gradient Method for Convex Optimization
Ellie Pond, April Sebok, Zachary Bell +1
We present a totally asynchronous algorithm for convex optimization that is based on a novel generalization of Nesterov's accelerated gradient method. This algorithm is developed f…
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…
Anomaly Search Over Many Sequences With Switching Costs
Matthew Ubl, Benjamin D. Robinson, Matthew T. Hale
This paper considers the quickest search problem to identify anomalies among large numbers of data streams. These streams can model, for example, disjoint regions monitored by a mo…
Cloud-Based Optimization: A Quasi-Decentralized Approach to Multi-Agent Coordination
Matthew Hale, Magnus Egerstedt
New architectures and algorithms are needed to reflect the mixture of local and global information that is available as multi-agent systems connect over the cloud. We present a nov…