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pro vyhledávání: '"Zhang, Leizhen"'
Its crux lies in the optimization of a tradeoff between accuracy and fairness of resultant models on the selected feature subset. The technical challenge of our setting is twofold: 1) streaming feature inputs, such that an informative feature may bec
Externí odkaz:
http://arxiv.org/abs/2408.12665
Quantifying uncertainties for machine learning models is a critical step to reduce human verification effort by detecting predictions with low confidence. This paper proposes a method for uncertainty quantification (UQ) of table structure recognition
Externí odkaz:
http://arxiv.org/abs/2407.01731