Papers › Accelerated Stochastic Gradient-free and Projection-free Methods

Accelerated Stochastic Gradient-free and Projection-free Methods

16 Jul 2020ICML 2020 1arXiv:2007.12625archive 2025-07-28

Feihu Huang, Lue Tao, Songcan Chen

In the paper, we propose a class of accelerated stochastic gradient-free and projection-free (a.k.a., zeroth-order Frank-Wolfe) methods to solve the constrained stochastic and finite-sum nonconvex optimization. Specifically, we propose an accelerated stochastic zeroth-order Frank-Wolfe (Acc-SZOFW) method based on the variance reduced technique of SPIDER/SpiderBoost and a novel momentum accelerated technique. Moreover, under some mild conditions, we prove that the Acc-SZOFW has the function query complexity of O(d√(n)ϵ⁻²) for finding an ϵ-stationary point in the finite-sum problem, which improves the exiting best result by a factor of O(√(n)ϵ⁻²), and has the function query complexity of O(dϵ⁻³) in the stochastic problem, which improves the exiting best result by a factor of O(ϵ⁻¹). To relax the large batches required in the Acc-SZOFW, we further propose a novel accelerated stochastic zeroth-order Frank-Wolfe (Acc-SZOFW*) based on a new variance reduced technique of STORM, which still reaches the function query complexity of O(dϵ⁻³) in the stochastic problem without relying on any large batches. In particular, we present an accelerated framework of the Frank-Wolfe methods based on the proposed momentum accelerated technique. The extensive experimental results on black-box adversarial attack and robust black-box classification demonstrate the efficiency of our algorithms.

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LMO_L1 TLMichael/Acc-SZOFW/app/utils.py official repository unverified MIT (permissive) · ebc01c301d7a3d83 · report
batch_compute_loss TLMichael/Acc-SZOFW/app/utils.py official repository unverified MIT (permissive) · ecb68471cb897bfd · report
batch_est_grad TLMichael/Acc-SZOFW/app/utils.py official repository unverified MIT (permissive) · bbfcead4b24970b1 · report
get_dataset TLMichael/Acc-SZOFW/app/datasets.py official repository unverified MIT (permissive) · b1d79112efd58522 · report
unison_shuffled_copies TLMichael/Acc-SZOFW/app/datasets.py official repository unverified MIT (permissive) · e28c2afa4ee0cfaa · report

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