From the 2 of 11 linked papers with an AI index.
11 papers
First-Order Optimization as Minimum-Time Control
Liraz Mudrik, Isaac Kaminer, Pramod P. Khargonekar
We formulate first-order optimization as a minimum-time control problem. The iterate is the state, the update, a combination of the gradients observed so far, is the control, and t…
Bang-Bang Evasion: Its Stochastic Optimality and a Terminal-Set-Based Implementation
Liraz Mudrik, Yaakov Oshman
The paper studies how a target can optimally evade a missile in a planar engagement under imperfect information and bounded controls, proving that bang‑bang maneuvers remain optima…
Mixed Bernstein-Fourier Approximants for Optimal Trajectory Generation with Periodic Behavior
Liraz Mudrik, Sean Kragelund, Isaac Kaminer
The paper proposes a mixed Bernstein-Fourier approximation framework for generating optimal trajectories that exhibit periodic behavior, providing convergence proofs, error analysi…
Comprehensive Approach to Directly Addressing Estimation Delays in Stochastic Guidance
Liraz Mudrik, Yaakov Oshman
In realistic pursuit-evasion scenarios, abrupt target maneuvers generate unavoidable periods of elevated uncertainty that result in estimation delays. Such delays can degrade inter…
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…
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…