Qin-Cheng Zheng — accepted AI-conference papers

2026

Theoretical Investigation on Inductive Bias of Isolation Forest

Qin-Cheng Zheng, Shao-Qun Zhang, Shen-Huan Lyu, Yuan Jiang, Zhi-Hua Zhou

ICML 2026poster

Isolation Forest (iForest) stands out as a widely-used unsupervised anomaly detector, primarily owing to its remarkable runtime efficiency and superior performance in large-scale tasks. Despite its widespread adoption, a theoretical foundation explaining iForest's success remains unclear. This paper…

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2023

On the Consistency Rate of Decision Tree Learning Algorithms

Qin-Cheng Zheng, Shen-Huan Lyu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou

AISTATS 2023poster

Decision tree learning algorithms such as CART are generally based on heuristics that maximizes the purity gain greedily. Though these algorithms are practically successful, theoretical properties such as consistency are far from clear. In this paper, we discover that the most serious obstacle encum…

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