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cs.LG2025
The Multi-Query Paradox in Zeroth-Order Optimization
Wei Lin, Qingyu Song, Hong Xu
Zeroth-order (ZO) optimization provides a powerful framework for problems where explicit gradients are unavailable and have to be approximated using only queries to function value.…
cs.LG2025
Towards Robust Learning to Optimize with Theoretical Guarantees
Qingyu Song, Wei Lin, Juncheng Wang +1
Learning to optimize (L2O) is an emerging technique to solve mathematical optimization problems with learning-based methods. Although with great success in many real-world scenario…
cs.LG2025
Learning Provably Improves the Convergence of Gradient Descent
Qingyu Song, Wei Lin, Hong Xu
Learn to Optimize (L2O) trains deep neural network-based solvers for optimization, achieving success in accelerating convex problems and improving non-convex solutions. However, L2…