3 papers
cs.LG2025
A Computational Approach to Improving Fairness in K-means Clustering
Guancheng Zhou, Haiping Xu, Hongkang Xu +2
The popular K-means clustering algorithm potentially suffers from a major weakness for further analysis or interpretation. Some cluster may have disproportionately more (or fewer)…
cs.LG2025
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark
Yili Wang, Yixin Liu, Xu Shen +6
To build safe and reliable graph machine learning systems, unsupervised graph-level anomaly detection (GLAD) and unsupervised graph-level out-of-distribution (OOD) detection (GLOD)…
cs.CV2025
PISA Experiments: Exploring Physics Post-Training for Video Diffusion Models by Watching Stuff Drop
Chenyu Li, Oscar Michel, Xichen Pan +3
Large-scale pre-trained video generation models excel in content creation but are not reliable as physically accurate world simulators out of the box. This work studies the process…