linear-minimization-oracle

This paper proposes LMO-IGT, a new class of stochastic optimization methods that accelerates convergence using implicit gradient transport while maintaining a single-gradient-per-iteration structure. It introduces a unified theoretical framework and demonstrates improved performance over existing LMO-based optimizers like Muon.