Three-average primal-dual methods achieve accelerated rates for computable accuracy certificates in convex optimization.
SIAM Journal on Optimization , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
verdicts
UNVERDICTED 2roles
background 1polarities
unclear 1representative citing papers
Proposes federated adaptive optimizers (FedAdagrad, FedAdam, FedYogi) with convergence analysis for non-convex objectives under data heterogeneity and reports empirical gains over FedAvg.
citing papers explorer
-
Accuracy Certificates for Convex Optimization at Accelerated Rates via Primal-Dual Averaging
Three-average primal-dual methods achieve accelerated rates for computable accuracy certificates in convex optimization.
-
Adaptive Federated Optimization
Proposes federated adaptive optimizers (FedAdagrad, FedAdam, FedYogi) with convergence analysis for non-convex objectives under data heterogeneity and reports empirical gains over FedAvg.