Abstract: As an emerging paradigm of federated learning, asynchronous federated learning offers significant speed advantages over traditional synchronous federated learning. Unlike synchronous ...
Abstract: Federated learning (FL) has been extensively studied as a means of ensuring data privacy while cooperatively training a global model across decentralized devices. Among various FL approaches ...
Minimax M2.5 lists $0.30 per million input tokens and $2.40 output on the lightning tier, helping builders plan predictable AI spend.
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