Trustworthy tree-based machine learning by MoS2 flash-based analog content-addressable memory with inherent soft boundaries
Bo Wen·C W. LI·Zhicheng Xu·Mingrui Jiang·Ruibin Mao·Xiaojuan Qi·Jiezhi Chen·Xunzhao Yin·X. Sharon Hu·Guoyun Gao
The rapid advancement of artificial intelligence has raised concerns regarding its trustworthiness, especially in terms of interpretability and robustness. Tree-based models such as Random Forest excel in interpretability and accuracy for tabular data, but scaling them remains computationally expensive due to poor data locality and high data dependence. Previous efforts to accelerate these models with analog content-addressable memory (CAM) have struggled because difficult-to-implement sharp dec
