Abstract: Deep reinforcement learning (DRL) facilitates efficient interaction with complex environments by enabling continuous optimization strategies and providing agents with autonomous learning ...
Sub‑100-ms APIs emerge from disciplined architecture using latency budgets, minimized hops, async fan‑out, layered caching, ...
Abstract: Edge computing has recently emerged as a promising paradigm to boost the performance of distributed learning by leveraging the distributed resources at edge nodes. Architecturally, the ...
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