collaborators

5 papers

math.OC2026

Saddle Point Evasion via Curvature-Regularized Gradient Dynamics

Liraz Mudrik, Isaac Kaminer, Sean Kragelund +1

Nonconvex optimization underlies many modern machine learning and control tasks, where saddle points pose the dominant obstacle to reliable convergence in high-dimensional settings…

math.OC2026

Prescribed-Time Distributed Generalized Nash Equilibrium Seeking

Liraz Mudrik, Isaac Kaminer, Sean Kragelund +1

Safety-critical multi-agent systems, from cooperative guidance to collision avoidance, must often reach a coordinated decision by a hard deadline rather than merely converge to one…

math.OC2026

Optimization via a Control-Centric Framework

Liraz Mudrik, Isaac Kaminer, Sean Kragelund +1

Optimization plays a central role in intelligent systems and cyber-physical technologies, where speed and reliability of convergence directly impact performance. In control theory,…

eess.SY2026

Scaling and Trade-offs in Multi-agent Autonomous Systems

Abram H. Clark, Liraz Mudrik, Colton Kawamura +3

Designing autonomous drone swarms is hampered by a vast design space spanning platform, algorithmic, and numerical-strength choices. We perform large-scale agent-based simulations…

cs.LG2025

Swarm Characteristics Classification Using Neural Networks

Donald W. Peltier, Isaac Kaminer, Abram Clark +1

Understanding the characteristics of swarming autonomous agents is critical for defense and security applications. This article presents a study on using supervised neural network…