We put forth a hybrid-computing solution to a class of constrained nonlinear optimization
problems involving nonlinear cost and linear constraints. This is accomplished by realizing …

We present a novel methodology for convex optimization algorithm design using ideas from
electric RLC circuits. Given an optimization problem, the first stage of the methodology is to …

Federated learning harnesses the power of distributed optimization to train a unified
machine learning model across separate clients. However, heterogeneous data distributions …