accelerated methods 1convex optimization 1entropy-smoothness 1lower bounds 1mirror descent 1quantum optimization 1
From the 1 of 3 linked papers with an AI index.
3 papers
math.OC2026
Entropy-Smooth Convex Optimization Cannot Be Accelerated
Jacob M. Aguirre, Dmitrii M. Ostrovskii
The paper proves that for convex functions that are smooth relative to negative entropy (or von Neumann entropy in the quantum case), no first-order method can achieve an accelerat…
math.OC2025
cuHALLaR: A GPU Accelerated Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming
Jacob M. Aguirre, Diego Cifuentes, Vincent Guigues +3
This paper introduces cuHALLaR, a GPU-accelerated implementation of the HALLaR method proposed in Monteiro et al. 2024 for solving large-scale semidefinite programming (SDP) proble…
math.OC2025
A User Manual for cuHALLaR: A GPU Accelerated Low-Rank Semidefinite Programming Solver
Jacob Aguirre, Diego Cifuentes, Vincent Guigues +3
We present a Julia-based interface to the precompiled HALLaR and cuHALLaR binaries for large-scale semidefinite programs (SDPs). Both solvers are established as fast and numericall…