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Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features.

, , , and . WSDM, page 1433-1442. ACM, (2022)

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Learning Fair Graph Neural Networks With Limited and Private Sensitive Attribute Information., and . IEEE Trans. Knowl. Data Eng., 35 (7): 7103-7117 (July 2023)Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network., , , , , and . CoRR, (2021)Learning Graph Filters for Spectral GNNs via Newton Interpolation., , , , and . CoRR, (2023)Labeled Data Generation with Inexact Supervision., , , and . KDD, page 218-226. ACM, (2021)A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy., , , , , , , and . KDD, page 368-379. ACM, (2023)Label-Wise Graph Convolutional Network for Heterophilic Graphs., , , and . LoG, volume 198 of Proceedings of Machine Learning Research, page 26. PMLR, (2022)Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels., , , and . WSDM, page 181-191. ACM, (2022)Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features., , , and . WSDM, page 1433-1442. ACM, (2022)Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series., and . ICLR, OpenReview.net, (2022)Unsupervised Image Super-Resolution with an Indirect Supervised Path., , , , , , , , , and . CVPR Workshops, page 1924-1933. Computer Vision Foundation / IEEE, (2020)