42 citations · 80 across the 9 of their papers we have counts for
4 papers · 1 filter
Rectified Decision Trees: Exploring the Landscape of Interpretable and Effective Machine Learning
Yiming Li, Jiawang Bai, Jiawei Li +3
Interpretability and effectiveness are two essential and indispensable requirements for adopting machine learning methods in reality. In this paper, we propose a knowledge distilla…
Toward Adversarial Robustness via Semi-supervised Robust Training
Yiming Li, Baoyuan Wu, Yan Feng +4
Adversarial examples have been shown to be the severe threat to deep neural networks (DNNs). One of the most effective adversarial defense methods is adversarial training (AT) thro…
--means: A Robust and Stable -means Variant
Yiming Li, Yang Zhang, Qingtao Tang +3
-means algorithm is one of the most classical clustering methods, which has been widely and successfully used in signal processing. However, due to the thin-tailed property of t…
Rectified Decision Trees: Towards Interpretability, Compression and Empirical Soundness
Jiawang Bai, Yiming Li, Jiawei Li +2
How to obtain a model with good interpretability and performance has always been an important research topic. In this paper, we propose rectified decision trees (ReDT), a knowledge…