17 citations · 27 across the 8 of their papers we have counts for
11 papers
SPPID: Saddle-Point PID for Constrained Optimization
Veronica Centorrino, Rawan Hoteit, Efe C. Balta +1
This paper studies constrained optimization problems through the lens of feedback control. Building on the interpretation of Lagrange multipliers as feedback controllers, we propos…
A Unified Control-Theoretic Framework for Saddle-Point Dynamics in Constrained Optimization
Veronica Centorrino, Rawan Hoteit, Efe C. Balta +1
This paper studies equality-constrained minimization problems through the lens of feedback control. We introduce a unified control-theoretic framework by showing that a PID feedbac…
An Energy-Based Mechanism for Compositional Behavior
Francesca Rossi, Veronica Centorrino, Francesco Bullo +1
Flexible intelligence relies on the ability to reuse previously acquired behaviors and combine them differently as circumstances change. In biological and artificial systems, this…
Similarity Matching Networks: Hebbian Learning and Convergence Over Multiple Time Scales
Veronica Centorrino, Francesco Bullo, Giovanni Russo
A recent breakthrough in biologically-plausible normative frameworks for dimensionality reduction is based upon the similarity matching cost function and the low-rank matrix approx…
Proximal Gradient Dynamics and Feedback Control for Equality-Constrained Composite Optimization
Veronica Centorrino, Francesca Rossi, Francesco Bullo +1
This paper studies equality-constrained composite minimization problems. This class of problems, capturing regularization terms and inequality constraints, naturally arises in a wi…
On Weakly Contracting Dynamics for Convex Optimization
Veronica Centorrino, Alexander Davydov, Anand Gokhale +2
We analyze the convergence behavior of \emph{globally weakly} and \emph{locally strongly contracting} dynamics. Such dynamics naturally arise in the context of convex optimization…
Positive Competitive Networks for Sparse Reconstruction
Veronica Centorrino, Anand Gokhale, Alexander Davydov +2
We propose and analyze a continuous-time firing-rate neural network, the positive firing-rate competitive network (\pfcn), to tackle sparse reconstruction problems with non-negativ…
Time-Varying Convex Optimization: A Contraction and Equilibrium Tracking Approach
Alexander Davydov, Veronica Centorrino, Anand Gokhale +2
In this article, we provide a novel and broadly-applicable contraction-theoretic approach to continuous-time time-varying convex optimization. For any parameter-dependent contracti…
Euclidean Contractivity of Neural Networks with Symmetric Weights
Veronica Centorrino, Anand Gokhale, Alexander Davydov +2
This paper investigates stability conditions of continuous-time Hopfield and firing-rate neural networks by leveraging contraction theory. First, we present a number of useful gene…
A numerically robust, parallel-friendly variant of BiCGSTAB for the semi-implicit integration of the viscous term in Smoothed Particle Hydrodynamics
Giuseppe Bilotta, Vito Zago, Veronica Centorrino +4
Implicit integration of the viscous term can significantly improve performance in computational fluid dynamics for highly viscous fluids such as lava. We show improvements over our…
Modeling and Contractivity of Neural-Synaptic Networks with Hebbian Learning
Veronica Centorrino, Francesco Bullo, Giovanni Russo
This paper is concerned with the modeling and analysis of two of the most commonly used recurrent neural network models (i.e., Hopfield neural network and firing-rate neural networ…