most citedGlobal Convergence of Second-order Dynamics in Two-layer Neural Networks

6 citations · 7 across the 3 of their papers we have counts for

collaborators

8 papers

math.OC20206 cited

Global Convergence of Second-order Dynamics in Two-layer Neural Networks

Walid Krichene, Kenneth F. Caluya, Abhishek Halder

Recent results have shown that for two-layer fully connected neural networks, gradient flow converges to a global optimum in the infinite width limit, by making a connection betwee…

math.OC2020

Reflected Schrödinger Bridge: Density Control with Path Constraints

Kenneth F. Caluya, Abhishek Halder

How to steer a given joint state probability density function to another over finite horizon subject to a controlled stochastic dynamics with hard state (sample path) constraints?…

math.OC2019

Finite Horizon Density Steering for Multi-input State Feedback Linearizable Systems

Kenneth F. Caluya, Abhishek Halder

In this paper, we study the feedback synthesis problem for steering the joint state density or ensemble subject to multi-input state feedback linearizable dynamics. This problem is…

math.OC2019

Proximal Recursion for the Wonham Filter

Abhishek Halder, Tryphon T. Georgiou

This paper contributes to the emerging viewpoint that governing equations for dynamic state estimation, conditioned on the history of noisy measurements, can be viewed as gradient…

math.OC2019

The Convex Geometry of Integrator Reach Sets

Shadi Haddad, Abhishek Halder

We study the convex geometry of the forward reach sets for integrator dynamics in finite dimensions with bounded control. We derive closed-form expressions for the volume and the d…

math.OC2019

Gradient Flow Algorithms for Density Propagation in Stochastic Systems

Kenneth F. Caluya, Abhishek Halder

We develop a new computational framework to solve the partial differential equations (PDEs) governing the flow of the joint probability density functions (PDFs) in continuous-time…