Distributed Learning with Selective State Space Models: Architecture-Aware Convergence Analysis
Modern state space models (SSMs), such as Mamba2, provide a compelling alternative to transformers by combining linear-time sequence modeling with recurrent state-space dynamics. However, the behavior of SSMs in distributed learning settings remains poorly understood. In particular, the existing standard federated lear...
Adam Piaseczny, Md Kamran Chowdhury Shisher, Shi-Qiang Wang et al.
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