Skew-symmetrically perturbed gradient flow for convex optimization - researchr publication authors

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Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Ikko Yamane. Skew-symmetrically perturbed gradient flow for convex optimization. In Vineeth N. Balasubramanian, Ivor W. Tsang, editors, Asian Conference on Machine Learning, ACML 2021, 17-19 November 2021, Virtual Event. Volume 157 of Proceedings of Machine Learning Research, pages 721-736, PMLR, 2021. [doi]

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