no code implementations • 26 Jul 2019 • Xiang Geng, Bin Gu, Xiang Li, Wanli Shi, Guansheng Zheng, Heng Huang
Specifically, to handle two types of data instances involved in S$^3$VM, TSGS$^3$VM samples a labeled instance and an unlabeled instance as well with the random features in each iteration to compute a triply stochastic gradient.
no code implementations • 29 Jul 2019 • Wanli Shi, Bin Gu, Xiang Li, Xiang Geng, Heng Huang
To address this problem, in this paper, we propose a novel scalable quadruply stochastic gradient algorithm (QSG-S2AUC) for nonlinear semi-supervised AUC optimization.
no code implementations • 24 Dec 2019 • Wanli Shi, Bin Gu, Xinag Li, Heng Huang
Semi-supervised ordinal regression (S$^2$OR) problems are ubiquitous in real-world applications, where only a few ordered instances are labeled and massive instances remain unlabeled.
no code implementations • 29 Sep 2021 • Wanli Shi, Hongchang Gao, Bin Gu
In this paper, to solve the nonconvex problem with a large number of white/black-box constraints, we proposed a doubly stochastic zeroth-order gradient method (DSZOG).
no code implementations • 29 Sep 2021 • Wanli Shi, Heng Huang, Bin Gu
Then, we transform the smoothed bi-level optimization to an unconstrained penalty problem by replacing the smoothed sub-problem with its first-order necessary conditions.