NISP: Pruning Networks using Neuron Importance Score Propagation

no code implementations • CVPR 2018 • Ruichi Yu, Ang Li, Chun-Fu Chen, Jui-Hsin Lai, Vlad I. Morariu, Xintong Han, Mingfei Gao, Ching-Yung Lin, Larry S. Davis

In contrast, we argue that it is essential to prune neurons in the entire neuron network jointly based on a unified goal: minimizing the reconstruction error of important responses in the "final response layer" (FRL), which is the second-to-last layer before classification, for a pruned network to retrain its predictive power.

Network Pruning

A Survey on Social Media Anomaly Detection

no code implementations • 6 Jan 2016 • Rose Yu, Huida Qiu, Zhen Wen, Ching-Yung Lin, Yan Liu

In this paper, we present a survey on existing approaches to address this problem.

Anomaly Detection