Showing 2026 · math.OCShow all
2 papers · 2 filters
math.OC2026
Peppy: An AI-Assisted Workflow for Tight Convergence Analysis of Optimization Algorithms
Jaewook J. Suh, TaeHo Yoon, Edward Duc Hien Nguyen +2
This paper presents Peppy, an AI-assisted workflow for discovering tight, analytic convergence proofs for first-order optimization algorithms. Generic approaches to using LLMs to c…
math.OC2026
Toward a Systematic Understanding and Interactive Search of Lyapunov-Style Proofs in Optimization
TaeHo Yoon, Jaewook J. Suh, Edward Duc Hien Nguyen +2
Lyapunov-style convergence proofs, which establish a nonincreasing sequence to provide a quantitative convergence rate for an algorithm, are popular and often considered desirable…