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Aug, 2024
难以解释:关于分布内模型解释的计算难度
Hard to Explain: On the Computational Hardness of In-Distribution Model Interpretation
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Guy Amir, Shahaf Bassan, Guy Katz
TL;DR
本研究针对机器学习模型解释能力的缺乏进行了深入探讨,提出了在解释模型时必须考虑底层分布这一重要因素。通过分析模型类型、解释形式和底层分布,研究显示底层分布的选择显著影响解释的复杂性,揭示了生成社会统一解释的必要前提。
Abstract
The ability to interpret
Machine Learning
(ML) models is becoming increasingly essential. However, despite significant progress in the field, there remains a lack of rigorous characterization regarding the innate
Interp
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