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Found 2 papers, 1 papers with code
Exploring the Learning Difficulty of Data Theory and Measure
As learning difficulty is crucial for machine learning (e. g., difficulty-based weighting learning strategies), previous literature has proposed a number of learning difficulty measures.
A Mathematical Foundation for Robust Machine Learning based on Bias-Variance Trade-off
Conducting a clear comparison for existing RML algorithms in dealing with different samples is difficult due to lack of a unified theoretical framework for RML.
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