Unverified50% confidenceFactExact time
The d·log p sample complexity is the advantageous order possessed by previous sharp methods that relied on subset search, and HOST achieves this level without sacrificing polynomial runtime.
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10/5/2026
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Related Claims
UnverifiedUnder appropriate conditions, HOST can exactly recover a DAG with p nodes and maximum in-degree d in polynomial time with sample complexity of order d·log p.78% similarUnverifiedHigh-dimensional structure learning of Gaussian DAGs faces a statistical-computational gap: methods with sharp sample complexity rely on computationally expensive subset searches and require a pre-specified in-degree upper bound, while polynomial-time algorithms exhibit comparatively inferior sample complexity.76% similarVerifiedHNSW reduces search complexity to approximately O(log n) by constructing a multi-layer graph index, while IVF partitions the vector space via K-means clustering to achieve orders-of-magnitude speed improvements at the cost of approximately 5–10% recall.74% similarUnverified精确的 K 近邻搜索（KNN）时间复杂度为 O(n×d)，在数百万级别记忆条目下延迟不可接受，ANN 算法通过牺牲极小精度换取数量级速度提升73% similarUnverifiedKolmogorov complexity refers to the true length of a piece of data being equal to the length of the shortest program that can generate it.73% similar
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