6 citations · 9 across the 8 of their papers we have counts for
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cs.LG2022★ 1 cited
Using Taylor-Approximated Gradients to Improve the Frank-Wolfe Method for Empirical Risk Minimization
Zikai Xiong, Robert M. Freund
The Frank-Wolfe method has become increasingly useful in statistical and machine learning applications, due to the structure-inducing properties of the iterates, and especially in…
cs.LG2022★ 1 cited
Learning from Multiple Annotator Noisy Labels via Sample-wise Label Fusion
Zhengqi Gao, Fan-Keng Sun, Mingran Yang +7
Data lies at the core of modern deep learning. The impressive performance of supervised learning is built upon a base of massive accurately labeled data. However, in some real-worl…