Primal-Dual First-Order Methods for Affinely Constrained Multi-block Saddle P…
We consider the convex-concave saddle point problem , where the decision variables and/or are subject to certain multi-block structure and affine coupling constraints, and possesses certain separa…
New First-Order Algorithms for Stochastic Variational Inequalities
In this paper, we propose two new solution schemes to solve the stochastic strongly monotone variational inequality (VI) problems: the stochastic extra-point solution scheme and the stochastic extr…
Adaptive Stochastic Variance Reduction for Subsampled Newton Method with Cubi…
The cubic regularized Newton method of Nesterov and Polyak has become increasingly popular for nonconvex optimization because of its capability of finding an approximate local solution with a secon…
An Optimal High-Order Tensor Method for Convex Optimization
This paper is concerned with finding an optimal algorithm for minimizing a composite convex objective function. The basic setting is that the objective is the sum of two convex functions: the first…
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