arXiv Machine Learning
Complexities of Weak Proximal Oracle Methods for Composite Convex Optimization
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arXiv Machine Learning
Sep 22
Accelerated stochastic first-order method for convex optimization under heavy-tailed noise
arXiv:2510.11676v2 Announce Type: replace-cross Abstract: We study convex composite optimization problems, where the objective function is given by the sum of a prox-friendly function and a convex fu...
arXiv Machine Learning
Jul 13
Accelerated Fully First-Order Methods for Bilevel and Minimax Optimization
arXiv:2405. 00914v4 Announce Type: replace-cross Abstract: We present in this paper novel accelerated fully first-order methods in \emph{Bilevel Optimization} (BLO).
arXiv Machine Learning
Jun 15
Lower Complexity Bounds for Nonconvex-Strongly-Convex Bilevel Optimization with First-Order Oracles
arXiv:2511. 19656v3 Announce Type: replace Abstract: Although upper bound guarantees for bilevel optimization have been widely studied, progress on lower bounds has been limited due to the complexity of the bilevel structure.
arXiv Machine Learning
Sep 10
Accelerated Frank-Wolfe Algorithms: Complementarity Conditions and Sparsity
arXiv:2511.02821v2 Announce Type: replace-cross Abstract: We develop new accelerated first-order algorithms in the Frank-Wolfe (FW) family for minimizing smooth convex functions over compact convex s...
arXiv Machine Learning
Jul 13
Nonconvex Composite Functional Constraints via First-Order Augmented Lagrangian Methods under Local Regularity
arXiv:2607. 08954v1 Announce Type: cross Abstract: We study nonasymptotic convergence of primal-dual methods for a class of nonconvex constrained optimization problems with a convex-composite structure.
arXiv Machine Learning
Sep 10
How to Make the Gradient Mapping Small for Constrained Stochastic Min-Max Problems and Beyond
arXiv:2609.08380v1 Announce Type: cross Abstract: We study the stochastic first-order oracle complexity for constrained or regularized convex-concave min-max optimization and stochastic monotone vari...