4 citations · 9 across the 7 of their papers we have counts for
3 papers · 1 filter
Kimad: Adaptive Gradient Compression with Bandwidth Awareness
Jihao Xin, Ivan Ilin, Shunkang Zhang +2
In distributed training, communication often emerges as a bottleneck. In response, we introduce Kimad, a solution that offers adaptive gradient compression. By consistently monitor…
Federated Learning is Better with Non-Homomorphic Encryption
Konstantin Burlachenko, Abdulmajeed Alrowithi, Fahad Ali Albalawi +1
Traditional AI methodologies necessitate centralized data collection, which becomes impractical when facing problems with network communication, data privacy, or storage capacity.…
Consensus-Based Optimization with Truncated Noise
Massimo Fornasier, Peter Richtárik, Konstantin Riedl +1
Consensus-based optimization (CBO) is a versatile multi-particle metaheuristic optimization method suitable for performing nonconvex and nonsmooth global optimizations in high dime…