New decision layer for expert model pools in streaming systems

This paper introduces a novel decision layer for streaming systems that manage pools of expert models. The layer intelligently decides whether to reuse an existing expert, spawn a new one, or defer based on statistical evidence. It is proven to maintain anytime validity and control multiplicity for an unbounded number of experts, demonstrating strong performance on synthetic datasets and benchmarks like Electricity, Covertype, and INSECTS. AI

IMPACT Introduces a statistically sound method for managing dynamic expert models in streaming AI systems.

RANK_REASON The item is an academic paper submitted to arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

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