Deep Active Learning by Model Interpretability

no code implementations • 23 Jul 2020 • Qiang Liu, Zhaocheng Liu, Xiaofang Zhu, Yeliang Xiu

In this paper, inspired by piece-wise linear interpretability in DNN, we introduce the linearly separable regions of samples to the problem of active learning, and propose a novel Deep Active learning approach by Model Interpretability (DAMI).

Active Learning Clustering +1