AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Random walk (RW)-based algorithms are widely used in decentralized learning due to their low communication overhead and scalability. While most existing methods rely on a single token, multiple tokens can explore the network in parallel and exchange information upon meeting. However, the fundamental benefits of such me...
A random-walk-based LoRA fine-tuning scheme that eliminates the need for global synchronization, substantially reduces communication and computation costs, and avoids aggregation errors is proposed and provides rigorous convergence guarantees for non-convex objectives under standard assumptions.
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