3 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 3 cited
Understand Data Preprocessing for Effective End-to-End Training of Deep Neural Networks
Ping Gong, Yuxin Ma, Cheng Li +2
In this paper, we primarily focus on understanding the data preprocessing pipeline for DNN Training in the public cloud. First, we run experiments to test the performance implicati…
cs.CV2022
One-Shot Medical Landmark Localization by Edge-Guided Transform and Noisy Landmark Refinement
Zihao Yin, Ping Gong, Chunyu Wang +2
As an important upstream task for many medical applications, supervised landmark localization still requires non-negligible annotation costs to achieve desirable performance. Besid…
cs.LG2022★ 3 cited
BiFeat: Supercharge GNN Training via Graph Feature Quantization
Yuxin Ma, Ping Gong, Jun Yi +4
Graph Neural Networks (GNNs) is a promising approach for applications with nonEuclidean data. However, training GNNs on large scale graphs with hundreds of millions nodes is both r…