collaborators

7 papers

math.OC2026

Boundedness of solutions in feedback systems with antithetic controllers

Moh Kamalul Wafi, Arthur C. B. de Oliveira, Eduardo D. Sontag

Antithetic feedback controllers have become a key experimental and theoretical tool in synthetic biology. Introduced by Khammash and collaborators about 10 years ago, they are empl…

math.OC2026

On incremental and semi-global exponential stability of gradient flows satisfying generalized Łojasiewicz inequalities

Andreas Oliveira, Arthur C. B. de Oliveira, Mario Sznaier +1

The Łojasiewicz inequality characterizes objective-value convergence along gradient flows and, in special cases, yields exponential decay of the cost. However, such results do not…

cs.LG2025

On the Convergence of Overparameterized Problems: Inherent Properties of the Compositional Structure of Neural Networks

Arthur Castello Branco de Oliveira, Dhruv Jatkar, Eduardo Sontag

This paper investigates how the compositional structure of neural networks shapes their optimization landscape and training dynamics. We analyze the gradient flow associated with o…

math.OC2025

On the (almost) Global Exponential Convergence of the Overparameterized Policy Optimization for the LQR Problem

Moh Kamalul Wafi, Arthur Castello B. de Oliveira, Eduardo D. Sontag

In this work we study the convergence of gradient methods for nonconvex optimization problems -- specifically the effect of the problem formulation to the convergence behavior of t…

math.OC2025

Safe-by-Design: Approximate Nonlinear Model Predictive Control with Real Time Feasibility

Jan Olucak, Arthur Castello B. de Oliveira, Torbjørn Cunis

This paper establishes relationships between continuous-time, receding horizon, nonlinear model predictive control (MPC) and control Lyapunov and control barrier functions (CLF/CBF…

eess.SY2025

Convergence Analysis of Gradient Flow for Overparameterized LQR Formulations

Arthur Castello B. de Oliveira, Milad Siami, Eduardo D. Sontag

Motivated by the growing use of artificial intelligence (AI) tools in control design, this paper analyses the intersection between results from gradient methods for the model-free…