Boosting the Performance of Decentralized Federated Learning via Catalyst Acceleration.

Li Q, Zhang M, Liu Y, Yin Q, Shen L, Cao X

Open source

DOI
10.1109/tpami.2026.3688672
Published
2026 Sep
Container
IEEE transactions on pattern analysis and machine intelligence
Publisher
Not recorded
Open access
unknown

Credibility signals

limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1109/tpami.2026.3688672,
  title = {Boosting the Performance of Decentralized Federated Learning via Catalyst Acceleration.},
  author = {Li Q and Zhang M and Liu Y and Yin Q and Shen L and Cao X},
  year = {2026},
  journal = {IEEE transactions on pattern analysis and machine intelligence},
  doi = {10.1109/tpami.2026.3688672},
  url = {https://doi.org/10.1109/tpami.2026.3688672}
}

RIS

TY  - JOUR
TI  - Boosting the Performance of Decentralized Federated Learning via Catalyst Acceleration.
AU  - Li Q
AU  - Zhang M
AU  - Liu Y
AU  - Yin Q
AU  - Shen L
AU  - Cao X
PY  - 2026
JO  - IEEE transactions on pattern analysis and machine intelligence
DO  - 10.1109/tpami.2026.3688672
UR  - https://doi.org/10.1109/tpami.2026.3688672
ER  - 

APA

Q, L., M, Z., Y, L., Q, Y., L, S., & X, C. (2026). Boosting the Performance of Decentralized Federated Learning via Catalyst Acceleration.. IEEE transactions on pattern analysis and machine intelligence. https://doi.org/10.1109/tpami.2026.3688672

Source records