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12/28/2022
Beyond the Golden Ratio for Variational Inequality Algorithms
We improve the understanding of the golden ratio algorithm, which solves...
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03/29/2022
Convergence and Complexity of Stochastic Subgradient Methods with Dependent Data for Nonconvex Optimization
We show that under a general dependent data sampling scheme, the classic...
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01/19/2022
On the Complexity of a Practical Primal-Dual Coordinate Method
We prove complexity bounds for the primal-dual algorithm with random ext...
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02/16/2021
Stochastic Variance Reduction for Variational Inequality Methods
We propose stochastic variance reduced algorithms for solving convex-con...
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07/13/2020
Random extrapolation for primal-dual coordinate descent
We introduce a randomly extrapolated primal-dual coordinate descent meth...
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07/07/2020
Conditional gradient methods for stochastically constrained convex minimization
We propose two novel conditional gradient-based methods for solving stru...
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06/11/2020
Convergence of adaptive algorithms for weakly convex constrained optimization
We analyze the adaptive first order algorithm AMSGrad, for solving a con...
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03/21/2020
A new regret analysis for Adam-type algorithms
In this paper, we focus on a theory-practice gap for Adam and its varian...
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11/09/2017