16 papers
Truncated Differentiation Through Primal-Dual Solvers for Inverse Potential Mean-Field Games
Siting Liu, Yat Tin Chow, Samy Wu Fung
We study inverse potential mean-field games (MFGs), in which an unknown spatial inverse-cost (mobility) map is inferred from observed population densities. We solve the forward MFG…
End-to-End Learning of Safe Optimal Feedback Control in High Dimensions with Control Barrier Function Layers
Xingjian Li, Kelvin Kan, Deepanshu Verma +3
We consider the problem of learning high-dimensional semi-global feedback controllers under hard safety constraints enforced by control barrier functions (CBFs). Incorporating CBFs…
Implicit Neural Optimal Transport via Fixed-Point Optimization
Yesom Park, Eric Gelphman, Stanley Osher +1
We propose an implicit neural formulation of optimal transport that eliminates adversarial min--max optimization and multi-network architectures commonly used in existing approache…
Probabilistic Gaussian Homotopy: A Probability-Space Continuation Framework for Nonconvex Optimization
Eshed Gal, Samy Wu Fung, Eldad Haber
We introduce Probabilistic Gaussian Homotopy (PGH), a probability-space continuation framework for nonconvex optimization. Unlike classical Gaussian homotopy, which smooths the obj…
Operator Splitting with Hamilton-Jacobi-based Proximals
Nicholas Di, Eric C. Chi, Samy Wu Fung
Operator splitting algorithms are a cornerstone of modern first-order optimization, decomposing complex problems into simpler subproblems solved via proximal operators. However, mo…
On the Convergence of Jacobian-Free Backpropagation for Optimal Control Problems with Implicit Hamiltonians
Eric Gelphman, Deepanshu Verma, Nicole Tianjiao Yang +2
Optimal feedback control with implicit Hamiltonians poses a fundamental challenge for learning-based value function methods due to the absence of closed-form optimal control laws.…