4 papers
Tractable Shapley Values and Interactions via Tensor Networks
Farzaneh Heidari, Chao Li, Guillaume Rabusseau
We show how to replace the O(2^n) coalition enumeration over n features behind Shapley values and Shapley-style interaction indices with a few-evaluation scheme on a tensor-network…
Graph-Based Uncertainty-Aware Self-Training with Stochastic Node Labeling
Tom Liu, Anna Wu, Chao Li
Self-training has become a popular semi-supervised learning technique for leveraging unlabeled data. However, the over-confidence of pseudo-labels remains a key challenge. In this…
Uncertainty-Aware Graph Self-Training with Expectation-Maximization Regularization
Emily Wang, Michael Chen, Chao Li
In this paper, we propose a novel \emph{uncertainty-aware graph self-training} approach for semi-supervised node classification. Our method introduces an Expectation-Maximization (…
Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix
Jintao Guo, Ying Zhou, Chao Li +1
When analyzing connection patterns within graphs, subgraph counting serves as an effective and fundamental approach. Edge-local differential privacy (edge-LDP) and shuffle model ha…