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20202023
most citedFedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation

305 citations · 741 across the 44 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

hep-ex2023

Observation of decay

M. Ablikim

Using a sample of events collected with the BESIII detector, the decay with subsequently decaying into $γπ^+…

hep-ex2023★ 3 cited

A coupled-channel analysis of the lineshape with BESIII data

BESIII Collaboration, M. Ablikim, M. N. Achasov +611

We perform a study of the lineshape using the data samples of , and collected with the BESIII detector. The…

hep-ex2023

Investigation of the rule and test of CP violation through the measurement of decay asymmetry parameters in decays

BESIII Collaboration, M. Ablikim, M. N. Achasov +615

Using events collected with the BESIII detector, numerous and decay asymmetry parameters are simultaneously determined from the process…

hep-ex2023★ 3 cited

Measurement of the cross sections from 2.000 to 3.080 GeV

BESIII Collaboration, M. Ablikim, M. N. Achasov +615

Based on collision data collected at center-of-mass energies from 2.000 to 3.080 GeV by the BESIII detector at the BEPCII collider, a partial wave analysis is performe…

cs.LG2023

FedSampling: A Better Sampling Strategy for Federated Learning

Tao Qi, Fangzhao Wu, Lingjuan Lyu +2

Federated learning (FL) is an important technique for learning models from decentralized data in a privacy-preserving way. Existing FL methods usually uniformly sample clients for…