6 citations · 14 across the 8 of their papers we have counts for
8 papers
On The Convergence of Euler Discretization of Finite-Time Convergent Gradient Flows
Siqi Zhang, Mouhacine Benosman, Orlando Romero
In this study, we investigate the performance of two novel first-order optimization algorithms, namely the rescaled-gradient flow (RGF) and the signed-gradient flow (SGF). These al…
A Dynamical Systems Approach for Convergence of the Bayesian EM Algorithm
Orlando Romero, Subhro Das, Pin-Yu Chen +1
Out of the recent advances in systems and control (S\&C)-based analysis of optimization algorithms, not enough work has been specifically dedicated to machine learning (ML) algorit…
Finite-Time Convergence of Continuous-Time Optimization Algorithms via Differential Inclusions
Orlando Romero, Mouhacine Benosman
In this paper, we propose two discontinuous dynamical systems in continuous time with guaranteed prescribed finite-time local convergence to strict local minima of a given cost fun…
Fractional-Order Model Predictive Control for Neurophysiological Cyber-Physical Systems: A Case Study using Transcranial Magnetic Stimulation
Orlando Romero, Sarthak Chatterjee, Sérgio Pequito
Fractional-order dynamical systems are used to describe processes that exhibit temporal long-term memory and power-law dependence of trajectories. There has been evidence that comp…
A Separation Principle for Discrete-Time Fractional-Order Dynamical Systems and its Implications to Closed-loop Neurotechnology
Sarthak Chatterjee, Orlando Romero, Sérgio Pequito
Closed-loop neurotechnology requires the capability to predict the state evolution and its regulation under (possibly) partial measurements. There is evidence that neurophysiologic…
Analysis of a Generalized Expectation-Maximization Algorithm for Gaussian Mixture Models: A Control Systems Perspective
Sarthak Chatterjee, Orlando Romero, Sérgio Pequito
The Expectation-Maximization (EM) algorithm is one of the most popular methods used to solve the problem of parametric distribution-based clustering in unsupervised learning. In th…
Convergence of the Expectation-Maximization Algorithm Through Discrete-Time Lyapunov Stability Theory
Orlando Romero, Sarthak Chatterjee, Sérgio Pequito
In this paper, we propose a dynamical systems perspective of the Expectation-Maximization (EM) algorithm. More precisely, we can analyze the EM algorithm as a nonlinear state-space…
Existence of positive solutions for an approximation of stationary mean-field games
Nojood Almayouf, Elena Bachini, Andreia Chapouto +22
Here, we consider a regularized mean-field game model that features a low-order regularization. We prove the existence of solutions with positive density. To do so, we combine a pr…