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Motivated by applications to distributed optimization over networks and large-scale data processing in machine learning, we analyze the deterministic incremental aggregated gradient method for minimizing a finite sum of smooth functions…

Optimization and Control · Mathematics 2018-01-16 Mert Gurbuzbalaban , Asuman Ozdaglar , Pablo Parrilo

This article establishes the existence of Lyapunov functions for analyzing the stability of a class of state-constrained systems, and it describes algorithms for their numerical computation. The system model consists of a differential…

Optimization and Control · Mathematics 2021-04-14 Marianne Souaiby , Aneel Tanwani , Didier Henrion

We present a new data-driven method to provide probabilistic stability guarantees for black-box switched linear systems. By sampling a finite number of observations of trajectories, we construct approximate Lyapunov functions and deduce the…

Optimization and Control · Mathematics 2021-05-04 Anne Rubbens , Zheming Wang , Raphaël M. Jungers

Value-based methods play a fundamental role in Markov decision processes (MDPs) and reinforcement learning (RL). In this paper, we present a unified control-theoretic framework for analyzing valued-based methods such as value computation…

Optimization and Control · Mathematics 2022-02-15 Xingang Guo , Bin Hu

Three similar convergence notions are considered. Two of them are the long established notions of convergent dynamics and incremental stability. The other is the more recent notion of contraction analysis. All three convergence notions…

Optimization and Control · Mathematics 2018-11-06 Duc N. Tran , Björn S. Rüffer , Christopher M. Kellett

First-order methods are often analyzed via their continuous-time models, where their worst-case convergence properties are usually approached via Lyapunov functions. In this work, we provide a systematic and principled approach to find and…

Numerical Analysis · Mathematics 2024-03-12 Céline Moucer , Adrien Taylor , Francis Bach

While global convergence of the Douglas-Rachford iteration is often observed in applications, proving it is still limited to convex and a handful of other special cases. Lyapunov functions for difference inclusions provide not only global…

Optimization and Control · Mathematics 2018-10-17 Ohad Giladi , Björn S. Rüffer

We study the behaviour of various Lyapunov functionals (relative entropies) along the solutions of a family of nonlinear drift-diffusion-reaction equations coming from statistical mechanics and population dynamics. These equations can be…

Functional Analysis · Mathematics 2019-04-09 Stanislav Kondratyev , Dmitry Vorotnikov

Piecewise-Linear in Rates (PWLR) Lyapunov functions are introduced for a class of Chemical Reaction Networks (CRNs). In addition to their simple structure, these functions are robust with respect to arbitrary monotone reaction rates, of…

Optimization and Control · Mathematics 2016-09-09 M. Ali Al-Radhawi , David Angeli

Switching between finitely many continuous-time autonomous steepest descent dynamics for convex functions is considered. Convergence of complete solutions to common minimizers of the convex functions, if such minimizers exist, is shown. The…

Optimization and Control · Mathematics 2018-08-06 Rafal Goebel , Ricardo Sanfelice

We consider an abstract class of infinite-dimensional dynamical systems with inputs. For this class, the significance of noncoercive Lyapunov functions is analyzed. It is shown that the existence of such Lyapunov functions implies…

Optimization and Control · Mathematics 2022-11-21 B. Jacob , A. Mironchenko , J. R. Partington , F. Wirth

We present a stability analysis framework for the general class of discrete-time linear switching systems for which the switching sequences belong to a regular language. They admit arbitrary switching systems as special cases. Using recent…

Dynamical Systems · Mathematics 2014-11-17 Matthew Philippe , Raphaël M. Jungers

We present a new approach for constructing polytope Lyapunov functions for continuous-time linear switching systems (LSS). This allows us to decide the stability of LSS and to compute the Lyapunov exponent with a good precision in…

Dynamical Systems · Mathematics 2014-06-24 Nicola Guglielmi , Linda Laglia , Vladimir Protasov

For systems evolving on a Riemannian manifold, we propose converse Lyapunov theorems for asymptotic and exponential stability. The novelty of the proposed approach is that is does not rely on local Euclidean coordinate, and is thus valid on…

Systems and Control · Electrical Eng. & Systems 2020-02-27 Dongjun Wu

This paper is concerned with stability analysis of nonlinear time-varying systems by using Lyapunov function based approach. The classical Lyapunov stability theorems are generalized in the sense that the time-derivative of the Lyapunov…

Dynamical Systems · Mathematics 2017-08-18 Bin Zhou

This paper is concerned with the study of synchronization and consensus phenomena in complex networks of diffusively-coupled nodes subject to external disturbances. Specifically, we make use of stochastic Lyapunov functions to provide…

Systems and Control · Computer Science 2016-03-22 Giovanni Russo , Rovert Shorten

This paper presents new sufficient conditions for convergence and asymptotic or exponential stability of a stochastic discrete-time system, under which the constructed Lyapunov function always decreases in expectation along the system's…

Systems and Control · Computer Science 2019-06-05 Yuzhen Qin , Ming Cao , Brian D. O. Anderson

A Path-Complete Lyapunov Function is an algebraic criterion composed of a finite number of functions, called its pieces, and a directed, labeled graph defining Lyapunov inequalities between these pieces. It provides a stability certificate…

Dynamical Systems · Mathematics 2016-12-14 David Angeli , Matthew Philippe , Nikolaos Athanasopoulos , Raphaël M. Jungers

We propose a composite Lyapunov framework for nonlinear autonomous systems that ensures strict decay through a pair of differential inequalities. The approach yields integral estimates, quantitative convergence rates, vanishing of…

Optimization and Control · Mathematics 2025-10-10 Hassan Saoud

This paper establishes risk convergence and asymptotic weight matrix alignment --- a form of implicit regularization --- of gradient flow and gradient descent when applied to deep linear networks on linearly separable data. In more detail,…

Machine Learning · Computer Science 2019-02-26 Ziwei Ji , Matus Telgarsky