Integration Methods and Optimization Algorithms

Part of Advances in Neural Information Processing Systems 30 (NIPS 2017)

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Damien Scieur, Vincent Roulet, Francis Bach, Alexandre d'Aspremont


We show that accelerated optimization methods can be seen as particular instances of multi-step integration schemes from numerical analysis, applied to the gradient flow equation. Compared with recent advances in this vein, the differential equation considered here is the basic gradient flow, and we derive a class of multi-step schemes which includes accelerated algorithms, using classical conditions from numerical analysis. Multi-step schemes integrate the differential equation using larger step sizes, which intuitively explains the acceleration phenomenon.