3 citations · 3 across the 3 of their papers we have counts for
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cs.LG2019
Unsupervised Co-Learning on -Manifolds Across Irreducible Representations
Yifeng Fan, Tingran Gao, Zhizhen Zhao
We introduce a novel co-learning paradigm for manifolds naturally equipped with a group action, motivated by recent developments on learning a manifold from attached fibre bundle s…
cs.LG2019★ 3 cited
SelectNet: Learning to Sample from the Wild for Imbalanced Data Training
Yunru Liu, Tingran Gao, Haizhao Yang
Supervised learning from training data with imbalanced class sizes, a commonly encountered scenario in real applications such as anomaly/fraud detection, has long been considered a…
cs.LG2019
Uniform-in-Time Weak Error Analysis for Stochastic Gradient Descent Algorithms via Diffusion Approximation
Yuanyuan Feng, Tingran Gao, Lei Li +2
Diffusion approximation provides weak approximation for stochastic gradient descent algorithms in a finite time horizon. In this paper, we introduce new tools motivated by the back…