Research graph
References from Privacy-Preserving Online Federated Learning for Massive Infinite Streams. Local targets link to admitted publications; unresolved targets remain external evidence.
10.1038/s41586-022-05172-4
10.1038/s41586-022-05172-4 · External reference
10.1038/s41586-022-04907-7
10.1038/s41586-022-04907-7 · External reference
10.1007/978-3-319-57959-7
10.1007/978-3-319-57959-7 · External reference
Communication-efficient learning of deep networks from decentralized data
External reference
10.1038/s41586-021-03583-3
10.1038/s41586-021-03583-3 · External reference
10.1038/s43588-021-00039-6
10.1038/s43588-021-00039-6 · External reference
10.1038/s41467-022-29763-x
10.1038/s41467-022-29763-x · External reference
10.1038/s41591-021-01506-3
10.1038/s41591-021-01506-3 · External reference
10.1038/s41467-022-32020-w
10.1038/s41467-022-32020-w · External reference
10.1109/cvpr52729.2023.01566
10.1109/cvpr52729.2023.01566 · External reference
10.1109/tii.2022.3200357
10.1109/tii.2022.3200357 · External reference
10.1609/aaai.v34i04.6125
10.1609/aaai.v34i04.6125 · External reference
10.1109/tits.2020.2986158
10.1109/tits.2020.2986158 · External reference
10.1109/tpami.2021.3129809
10.1109/tpami.2021.3129809 · External reference
10.52202/068431-2414
10.52202/068431-2414 · External reference
10.1145/3527621
10.1145/3527621 · External reference
10.1109/sp.2019.00029
10.1109/sp.2019.00029 · External reference
10.1109/sp.2017.41
10.1109/sp.2017.41 · External reference
10.1109/tmc.2024.3417930
10.1109/tmc.2024.3417930 · External reference
10.1145/1806689.1806787
10.1145/1806689.1806787 · External reference
10.2478/popets-2021-0013
10.2478/popets-2021-0013 · External reference
10.29012/jpc.718
10.29012/jpc.718 · External reference
10.1038/s42256-021-00337-8
10.1038/s42256-021-00337-8 · External reference
10.1145/3383455.3422562
10.1145/3383455.3422562 · External reference
10.1109/tifs.2018.2812146
10.1109/tifs.2018.2812146 · External reference
10.14778/2732977.2732989
10.14778/2732977.2732989 · External reference
10.24963/ijcai.2021/217
10.24963/ijcai.2021/217 · External reference
10.1038/s41467-023-38794-x
10.1038/s41467-023-38794-x · External reference
10.1109/mnet.001.2200204
10.1109/mnet.001.2200204 · External reference
10.1109/bigdata50022.2020.9378161
10.1109/bigdata50022.2020.9378161 · External reference
10.1561/9781680831719
10.1561/9781680831719 · External reference
10.1109/icassp43922.2022.9746228
10.1109/icassp43922.2022.9746228 · External reference
10.1109/tpami.2023.3316672
10.1109/tpami.2023.3316672 · External reference
10.1109/jiot.2024.3363181
10.1109/jiot.2024.3363181 · External reference
10.1109/icc45855.2022.9839079
10.1109/icc45855.2022.9839079 · External reference
10.1007/978-3-540-79228-4_1
10.1007/978-3-540-79228-4_1 · External reference
10.18653/v1/2023.acl-industry.60
10.18653/v1/2023.acl-industry.60 · External reference
10.1145/3801079
10.1145/3801079 · External reference
10.1145/3650028
10.1145/3650028 · External reference
10.52202/075280-2639
10.52202/075280-2639 · External reference
10.1177/20552076251358531
10.1177/20552076251358531 · External reference
10.1145/2976749.2978318
10.1145/2976749.2978318 · External reference
10.1609/aaai.v35i10.17053
10.1609/aaai.v35i10.17053 · External reference
10.1137/1.9781611975482.151
10.1137/1.9781611975482.151 · External reference
Shuffled model of differential privacy in federated learning
External reference
Privacy amplification via random check-ins
External reference
10.1109/tsp.2025.3553355
10.1109/tsp.2025.3553355 · External reference
Revisiting differentially private algorithms for decentralized online learning
External reference
ScaleCom: Scalable sparsified gradient compression for communication-efficient distributed training
External reference
10.1137/20m1355847
10.1137/20m1355847 · External reference
10.1109/mcom.001.1900594
10.1109/mcom.001.1900594 · External reference
10.52202/079017-0891
10.52202/079017-0891 · External reference
Towards understanding biased client selection in federated learning
External reference
CMFL: Mitigating communication overhead for federated learning
External reference
Oort: Efficient federated learning via guided participant selection
External reference
10.1109/tpds.2022.3230938
10.1109/tpds.2022.3230938 · External reference
10.1007/978-3-030-59410-7_33
10.1007/978-3-030-59410-7_33 · External reference
10.1109/tkde.2018.2794384
10.1109/tkde.2018.2794384 · External reference
10.1109/jiot.2021.3089713
10.1109/jiot.2021.3089713 · External reference
10.1145/3514221.3526190
10.1145/3514221.3526190 · External reference
10.1038/nature14236
10.1038/nature14236 · External reference
10.1109/infocom41043.2020.9155494
10.1109/infocom41043.2020.9155494 · External reference
Unresolved reference
2018 · External reference
10.1609/aaai.v30i1.10295
10.1609/aaai.v30i1.10295 · External reference
10.24963/ijcai.2017/483
10.24963/ijcai.2017/483 · External reference
10.1561/9781680837896
10.1561/9781680837896 · External reference
10.1038/s41597-022-01122-x
10.1038/s41597-022-01122-x · External reference
10.1109/tdsc.2016.2599873
10.1109/tdsc.2016.2599873 · External reference
Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach
External reference
Personalized federated learning with moreau envelopes
External reference
