扩展前的证据：终身专家池中的重用、生成或弃权（不执行）
Evidence Before Expansion: Reuse, Spawn, or Defer in Lifelong Expert Pools
- Center for Management of Information Technologies, Kagoshima University（鹿儿岛大学信息管理中心）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
该研究提出终身专家池的决策层，通过重启的e检测器实现零错误生成与重用，在多概念流基准上性能优于窗口启发式算法，保证了统计有效性。
AI中文摘要：
维护专家模型池的流式系统必须反复决定是为到达的数据重用现有专家、生成新专家还是弃权（不执行）。我们提出一个决策层，使这三种结果都具有统计意义。重用和生成被表述为关于条件（机制层面）差异的单侧序贯假设，由一个无差异区间分隔；弃权（不执行）恰好是两个投注e过程均未积累足够证据的状态。我们证明了可预测判别器序列的可观测替代差异具有有限时间的任意时间有效性，且无条件单侧转移到总体量，其中每一侧的松弛是单个判别器的超额风险；经验观察到的向下偏差正则性使生成侧恰好保守。通过重启的e检测器获得不牺牲保证的时效性：一组在几何间隔重启时间的无窗口投注上鞅（内存为O(log t)），误差预算在重启实例间分配，这保留了终身任意时间有效性；在专家创建顺序上分配预算同样控制了无限多专家的多重性。在合成多概念流、Electricity、Covertype和重复率高的INSECTS基准上，考虑实例的重启组在切换后实现了零错误生成和零错误重用，且在INSECTS重复精度（0.675）上匹配或超过了已弃用的窗口启发式算法，使部署算法与保证算法一致。
英文摘要：
Streaming systems that maintain a pool of expert models must repeatedly decide whether to reuse an existing expert for arriving data, spawn a new one, or defer. We present a decision layer that makes all three outcomes statistically meaningful. Reuse and spawn are posed as one-sided sequential hypotheses on a conditional (mechanism-level) discrepancy, separated by an indifference zone; defer is exactly the state in which neither betting e-process has accumulated sufficient evidence. We prove finite-time anytime validity for the observable surrogate discrepancy of a predictable discriminator sequence, and an unconditional one-sided transfer to the population quantity in which each side's slack is the excess risk of a single discriminator; an empirically observed downward-bias regularity makes the spawn side exactly conservative. Recency without sacrificing the guarantee is obtained by a restarted e-detector: a bank of unwindowed betting supermartingales at geometrically spaced restart times (O(log t) memory), with the error budget spent over restart instances, which preserves lifetime anytime validity; spending over expert-creation order likewise controls multiplicity for unboundedly many experts. On synthetic multi-concept streams, Electricity, Covertype, and the recurrence-heavy INSECTS benchmark, the instance-accounted restarted bank achieves zero false spawns and zero false reuses after switches and matches or exceeds the retired windowed heuristic (INSECTS-reoccurring accuracy 0.675), making the deployed algorithm and the guaranteed algorithm one and the same.
