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Applying Robust Gradient Difference Compression to Federated Learning.

, , , and . CSCWD, page 1748-1753. IEEE, (2023)

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Fast and Scalable Estimator for Sparse and Unit-Rank Higher-Order Regression Models., and . CoRR, (2019)Scalable Estimator for Multi-task Gaussian Graphical Models Based in an IoT Network., , , , and . ACM Trans. Sens. Networks, 17 (3): 23:1-23:33 (2021)GaKCo: A Fast Gapped k-mer String Kernel Using Counting., , , , , and . ECML/PKDD (1), volume 10534 of Lecture Notes in Computer Science, page 356-373. Springer, (2017)A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models., , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 5148-5157. PMLR, (2018)Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure., , and . AISTATS, volume 84 of Proceedings of Machine Learning Research, page 1691-1700. PMLR, (2018)Graph Inference via the Energy-efficient Dynamic Precision Matrix Estimation with One-bit Data., , , and . CIKM, page 2382-2391. ACM, (2023)Fast and scalable learning of sparse changes in high-dimensional graphical model structure., , , and . Neurocomputing, (2022)DeepCloak: Masking Deep Neural Network Models for Robustness Against Adversarial Samples., , , , and . ICLR (Workshop), OpenReview.net, (2017)Collaborative Estimating Multiple Gaussian Graphical Models on Resource Constrained Devices in IoT Networks., and . SMC, page 3583-3588. IEEE, (2023)A Framework Using Absolute Compression Hard-Threshold for Improving The Robustness of Federated Learning Model., and . CSCWD, page 1106-1111. IEEE, (2023)