7 citations · 24 across the 7 of their papers we have counts for
8 papers
Computer-aided analyses of stochastic first-order methods, via interpolation conditions for stochastic optimization
Anne Rubbens, Sébastien Colla, Julien M. Hendrickx
This work proposes a framework, embedded within the Performance Estimation framework (PEP), for obtaining worst-case performance guarantees on stochastic first-order methods. Given…
Analysis of Value Iteration Through Absolute Probability Sequences
Arsenii Mustafin, Sebastien Colla, Alex Olshevsky +1
Value Iteration is a widely used algorithm for solving Markov Decision Processes (MDPs). While previous studies have extensively analyzed its convergence properties, they primarily…
Exploiting Agent Symmetries for Performance Analysis of Distributed Optimization Methods
Sebastien Colla, Julien M. Hendrickx
We show that, in many settings, the worst-case performance of a distributed optimization algorithm is independent of the number of agents in the system, and can thus be computed in…
On the Optimal Communication Weights in Distributed Optimization Algorithms
Sebastien Colla, Julien M. Hendrickx
We establish that in distributed optimization, the prevalent strategy of minimizing the second-largest eigenvalue modulus (SLEM) of the averaging matrix for selecting communication…
Interpolation Constraints for Computing Worst-Case Bounds in Performance Estimation Problems
Anne Rubbens, Nizar Bousselmi, Sebastien Colla +1
The Performance Estimation Problem (PEP) approach consists in computing worst-case performance bounds on optimization algorithms by solving an optimization problem: one maximizes a…
Automated Performance Estimation for Decentralized Optimization via Network Size Independent Problems
Sebastien Colla, Julien M. Hendrickx
We develop a novel formulation of the Performance Estimation Problem (PEP) for decentralized optimization whose size is independent of the number of agents in the network. The PEP…
Automatic Performance Estimation for Decentralized Optimization
Sebastien Colla, Julien M. Hendrickx
We present a methodology to automatically compute worst-case performance bounds for a large class of first-order decentralized optimization algorithms. These algorithms aim at mini…
Automated Worst-Case Performance Analysis of Decentralized Gradient Descent
Sebastien Colla, Julien M. Hendrickx
We develop a methodology to automatically compute worst-case performance bounds for a class of decentralized algorithms that optimize the average of local functions distributed acr…