260 citations · 392 across the 22 of their papers we have counts for
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cs.CV2022★ 1 cited
Turning a Curse into a Blessing: Enabling In-Distribution-Data-Free Backdoor Removal via Stabilized Model Inversion
Si Chen, Yi Zeng, Jiachen T. Wang +5
Many backdoor removal techniques in machine learning models require clean in-distribution data, which may not always be available due to proprietary datasets. Model inversion techn…
cs.AI2022★ 2 cited
Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation
Kai Zhang, Yu Wang, Hongyi Wang +4
Federated learning (FL) can be essential in knowledge representation, reasoning, and data mining applications over multi-source knowledge graphs (KGs). A recent study FedE first pr…
cs.LG2022★ 2 cited
Gromov-Wasserstein Discrepancy with Local Differential Privacy for Distributed Structural Graphs
Hongwei Jin, Xun Chen
Learning the similarity between structured data, especially the graphs, is one of the essential problems. Besides the approach like graph kernels, Gromov-Wasserstein (GW) distance…