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The global rate of convergence for optimal tensor methods in smooth convex optimization

, , , , , and . (2018)cite arxiv:1809.00382Comment: In the current version we present a translation into English of the main derivations, which first appeared on September 2, 2018 in Russian, extend the analysis from the case of strongly convex objective to the case of uniformly convex objectives and add the numerical analysis of our results.

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The global rate of convergence for optimal tensor methods in smooth convex optimization, , , , , and . (2018)cite arxiv:1809.00382Comment: In the current version we present a translation into English of the main derivations, which first appeared on September 2, 2018 in Russian, extend the analysis from the case of strongly convex objective to the case of uniformly convex objectives and add the numerical analysis of our results.Accelerated Gradient-Free Optimization Methods with a Non-Euclidean Proximal Operator., , , and . Autom. Remote. Control., 80 (8): 1487-1501 (2019)Extended Separating Plane Algorithm and NSO-Solutions of PageRank Problem.. DOOR, volume 9869 of Lecture Notes in Computer Science, page 547-560. Springer, (2016)Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives., , , , , , , , , and 4 other author(s). COLT, volume 99 of Proceedings of Machine Learning Research, page 1392-1393. PMLR, (2019)Oracle Complexity Separation in Convex Optimization., , , , , , and . J. Optim. Theory Appl., 193 (1): 462-490 (2022)Convex optimization., , , and . CoRR, (2021)Optimal Tensor Methods in Smooth Convex and Uniformly ConvexOptimization., , , , , and . COLT, volume 99 of Proceedings of Machine Learning Research, page 1374-1391. PMLR, (2019)Accelerated Directional Search with Non-Euclidean Prox-Structure., , and . Autom. Remote. Control., 80 (4): 693-707 (2019)