1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 1 cited
Fully Exploiting Every Real Sample: SuperPixel Sample Gradient Model Stealing
Yunlong Zhao, Xiaoheng Deng, Yijing Liu +3
Model stealing (MS) involves querying and observing the output of a machine learning model to steal its capabilities. The quality of queried data is crucial, yet obtaining a large…
cs.LG2024★ 1 cited
Graph Diffusion Policy Optimization
Yijing Liu, Chao Du, Tianyu Pang +3
Recent research has made significant progress in optimizing diffusion models for downstream objectives, which is an important pursuit in fields such as graph generation for drug de…
cs.HC2020
GraphFederator: Federated Visual Analysis for Multi-party Graphs
Dongming Han, Wei Chen, Rusheng Pan +8
This paper presents GraphFederator, a novel approach to construct joint representations of multi-party graphs and supports privacy-preserving visual analysis of graphs. Inspired by…