4 citations · 6 across the 5 of their papers we have counts for
5 papers
Cosine Model Watermarking Against Ensemble Distillation
Laurent Charette, Lingyang Chu, Yizhou Chen +3
Many model watermarking methods have been developed to prevent valuable deployed commercial models from being stealthily stolen by model distillations. However, watermarks produced…
An Optimal Resource Allocator of Elastic Training for Deep Learning Jobs on Cloud
Liang Hu, Jiangcheng Zhu, Zirui Zhou +3
Cloud training platforms, such as Amazon Web Services and Huawei Cloud provide users with computational resources to train their deep learning jobs. Elastic training is a service e…
Auto-Split: A General Framework of Collaborative Edge-Cloud AI
Amin Banitalebi-Dehkordi, Naveen Vedula, Jian Pei +3
In many industry scale applications, large and resource consuming machine learning models reside in powerful cloud servers. At the same time, large amounts of input data are collec…
Finding Representative Interpretations on Convolutional Neural Networks
Peter Cho-Ho Lam, Lingyang Chu, Maxim Torgonskiy +3
Interpreting the decision logic behind effective deep convolutional neural networks (CNN) on images complements the success of deep learning models. However, the existing methods c…
Data Pricing in Machine Learning Pipelines
Zicun Cong, Xuan Luo, Pei Jian +2
Machine learning is disruptive. At the same time, machine learning can only succeed by collaboration among many parties in multiple steps naturally as pipelines in an eco-system, s…