RNNRepair: Automatic RNN Repair via Model-based Analysis
Xiaofei Xie 1 2 Wenbo Guo 3 Lei Ma 4 5 2 Wei Le 6 Jian Wang 1 Lingjun Zhou 7 Xinyu Xing 3 Yang Liu 1
Abstract the wrong prediction (Koh & Liang, 2017). Once the root
cause is identified, users may fix the errors by removing
Deep neural networks are vulnerable to adversar-
harmful training data or adding specific data to improve
ial a ...


雷达卡




京公网安备 11010802022788号







