52 citations · 111 across the 30 of their papers we have counts for
5 papers · 1 filter
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…
Contractivity of Distributed Optimization and Nash Seeking Dynamics
Anand Gokhale, Alexander Davydov, Francesco Bullo
In this letter, we study distributed optimization and Nash equilibrium-seeking dynamics from a contraction theoretic perspective. Our first result is a novel bound on the logarithm…
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…
Non-Euclidean Monotone Operator Theory and Applications
Alexander Davydov, Saber Jafarpour, Anton V. Proskurnikov +1
While monotone operator theory is often studied on Hilbert spaces, many interesting problems in machine learning and optimization arise naturally in finite-dimensional vector space…
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…