24 citations · 54 across the 7 of their papers we have counts for
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cs.LG2021★ 24 cited
NetFense: Adversarial Defenses against Privacy Attacks on Neural Networks for Graph Data
I-Chung Hsieh, Cheng-Te Li
Recent advances in protecting node privacy on graph data and attacking graph neural networks (GNNs) gain much attention. The eye does not bring these two essential tasks together y…
cs.LG2021★ 1 cited
FinGAT: Financial Graph Attention Networks for Recommending Top-K Profitable Stocks
Yi-Ling Hsu, Yu-Che Tsai, Cheng-Te Li
Financial technology (FinTech) has drawn much attention among investors and companies. While conventional stock analysis in FinTech targets at predicting stock prices, less effort…
cs.SI2021
CoANE: Modeling Context Co-occurrence for Attributed Network Embedding
I-Chung Hsieh, Cheng-Te Li
Attributed network embedding (ANE) is to learn low-dimensional vectors so that not only the network structure but also node attributes can be preserved in the embedding space. Exis…