Image de couverture de livre

A constructive approach to strengthen algebraic descriptions of function and operator classes

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Rubbens, Anne, Hendrickx, Julien M., Taylor, Adrien
Format:	Preprint
Publié:	2025
Sujets:	Optimization and Control
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

A constraint-based approach to function interpolation, with application to performance estimation for weakly convex optimisation
par: Rubbens, Anne, et autres
Publié: (2024)

Computer-aided analyses of stochastic first-order methods, via interpolation conditions for stochastic optimization
par: Rubbens, Anne, et autres
Publié: (2025)

Interpolation Constraints for Computing Worst-Case Bounds in Performance Estimation Problems
par: Rubbens, Anne, et autres
Publié: (2023)

Performance Estimation of second-order optimization methods on classes of univariate functions
par: Rubbens, Anne, et autres
Publié: (2025)

Counter-examples in first-order optimization: a constructive approach
par: Goujaud, Baptiste, et autres
Publié: (2023)

Path-Based Conditions for the Identifiability of Non-additive Nonlinear Networks with Full Measurements
par: Vizuete, Renato, et autres
Publié: (2025)

Local Identifiability of Fully-Connected Feed-Forward Networks with Nonlinear Node Dynamics
par: Vanelli, Martina, et autres
Publié: (2024)

Nonlinear identifiability of directed acyclic graphs with partial excitation and measurement
par: Vizuete, Renato, et autres
Publié: (2024)

Nonlinear Network Identifiability with Full Excitations
par: Vizuete, Renato, et autres
Publié: (2024)

Consensus on Open Multi-Agent Systems Over Graphs Sampled from Graphons
par: Vizuete, Renato, et autres
Publié: (2025)

On the Set of Possible Minimizers of a Sum of Convex Functions
par: Zamani, Moslem, et autres
Publié: (2024)

On the Optimal Communication Weights in Distributed Optimization Algorithms
par: Colla, Sebastien, et autres
Publié: (2024)

Exploiting Agent Symmetries for Performance Analysis of Distributed Optimization Methods
par: Colla, Sebastien, et autres
Publié: (2024)

Identification of Nonlinear Acyclic Networks in Continuous Time from Nonzero Initial Conditions and Full Excitations
par: Anantharaman, Ramachandran, et autres
Publié: (2026)

Interpolation Conditions for Data Consistency and Prediction in Noisy Linear Systems
par: Vanelli, Martina, et autres
Publié: (2025)

Comparison of Proximal First-Order Primal and Primal-Dual algorithms via Performance Estimation
par: Bousselmi, Nizar, et autres
Publié: (2024)

PEPit: computer-assisted worst-case analyses of first-order optimization methods in Python
par: Goujaud, Baptiste, et autres
Publié: (2022)

On the Convex Interpolation for Linear Operators
par: Bousselmi, Nizar, et autres
Publié: (2025)

Numerical Design of Optimized First-Order Algorithms
par: Kamri, Yassine, et autres
Publié: (2025)

Data Poisoning Attacks Can Systematically Destabilize Data-Driven Control Synthesis
par: Digge, Vijayanand, et autres
Publié: (2026)

Open Problem: Two Riddles in Heavy-Ball Dynamics
par: Goujaud, Baptiste, et autres
Publié: (2025)

Provable non-accelerations of the heavy-ball method
par: Goujaud, Baptiste, et autres
Publié: (2023)

On the Worst-Case Analysis of Cyclic Block Coordinate Descent type Algorithms
par: Kamri, Yassine, et autres
Publié: (2025)

Several Performance Bounds on Decentralized Online Optimization are Highly Conservative and Potentially Misleading
par: Meunier, Erwan, et autres
Publié: (2025)

On the convergence rate of the boosted Difference-of-Convex Algorithm (DCA)
par: Abbaszadehpeivasti, Hadi, et autres
Publié: (2025)

On extending the class of convex functions
par: Mohan, Shravan
Publié: (2025)

A general approach to distributed operator splitting
par: Dao, Minh N., et autres
Publié: (2025)

Nonlinear conjugate gradient methods: worst-case convergence rates via computer-assisted analyses
par: Gupta, Shuvomoy Das, et autres
Publié: (2023)

Automated tight Lyapunov analysis for first-order methods
par: Upadhyaya, Manu, et autres
Publié: (2023)

A Tight Theory of Error Feedback Algorithms in Distributed Optimization
par: Thomsen, Daniel Berg, et autres
Publié: (2026)

On a group of invariances in a class of functions
par: Mohan, Shravan
Publié: (2026)

Augmented Lagrangian methods for infeasible convex optimization problems and diverging proximal-point algorithms
par: Andrews, Roland, et autres
Publié: (2025)

An optimal first-order method for smooth and strongly convex composite optimization and its stationary limit
par: Upadhyaya, Manu, et autres
Publié: (2026)

Global minimisation of nonconvex functions by generalising the mirror descent method
par: Millán, Reinier Díaz, et autres
Publié: (2024)

Guardian maps for continuous-time systems: A Lie-algebraic approach
par: Bar-Shalom, Eyal, et autres
Publié: (2025)

On universal classes of Lyapunov functions for linear switched systems
par: Mason, Paolo, et autres
Publié: (2022)

Directional first order approach for a class of bilevel programs
par: Bai, Kuang, et autres
Publié: (2026)

Concave tents: a new tool for constructing concave reformulations of a large class of nonconvex optimization problems
par: Gabl, Markus
Publié: (2024)

Data-driven control of continuous-time systems: A synthesis-operator approach
par: Wakaiki, Masashi
Publié: (2025)

A Choice-Driven Service Network Design and Pricing Including Heterogeneous Behaviors
par: Nicolet, Adrien, et autres
Publié: (2023)