273 citations · 833 across the 12 of their papers we have counts for
8 papers · 1 filter
Accelerated Learning with Robustness to Adversarial Regressors
Joseph E. Gaudio, Anuradha M. Annaswamy, José M. Moreu +2
High order momentum-based parameter update algorithms have seen widespread applications in training machine learning models. Recently, connections with variational approaches have…
Connections Between Adaptive Control and Optimization in Machine Learning
Joseph E. Gaudio, Travis E. Gibson, Anuradha M. Annaswamy +2
This paper demonstrates many immediate connections between adaptive control and optimization methods commonly employed in machine learning. Starting from common output error formul…
Provably Correct Learning Algorithms in the Presence of Time-Varying Features Using a Variational Perspective
Joseph E. Gaudio, Travis E. Gibson, Anuradha M. Annaswamy +1
Features in machine learning problems are often time-varying and may be related to outputs in an algebraic or dynamical manner. The dynamic nature of these machine learning problem…
Impacts of Network Topology on the Performance of a Distributed Algorithm Solving Linear Equations
Hong-Tai Cao, Travis E. Gibson, Shaoshuai Mou +1
Recently a distributed algorithm has been proposed for multi-agent networks to solve a system of linear algebraic equations, by assuming each agent only knows part of the system an…
Sign Stability via Root Locus Analysis
Travis E. Gibson
With the rise of network science old topics in ecology and economics are resurfacing. One such topic is structural stability (often referred to as qualitative stability or sign sta…
Convergence Properties of Adaptive Systems and the Definition of Exponential Stability
Benjamin M. Jenkins, Anuradha M. Annaswamy, Eugene Lavretsky +1
The convergence properties of adaptive systems in terms of excitation conditions on the regressor vector are well known. With persistent excitation of the regressor vector in model…
Closed-loop Reference Models for Output-Feedback Adaptive Systems
Travis E. Gibson, Anuradha M. Annaswamy, Eugene Lavretsky
Closed-loop reference models have recently been proposed for states accessible adaptive systems. They have been shown to have improved transient response over their open loop count…
Adaptive Systems with Closed-loop Reference Models: Stability, Robustness and Transient Performance
Travis E. Gibson, Anuradha M. Annaswamy, Eugene Lavretsky
This paper explores the properties of adaptive systems with closed-loop reference models. Using additional design freedom available in closed-loop reference models, we design new a…