LCS Publication Details
Publication Title: Learning from Imperfect Data in Theory and Practice
Publication Author: Slonim, D.K.
Additional Authors:
LCS Document Number: MIT-LCS-TR-690
Publication Date: 5-1-1996
LCS Group: Theory of Computation
Additional URL: No URL Given
This thesis explores several problems of learning with noisy or incomplete data. Most machine learning applications need to infer correct conclusions from available information, although some data may be incorrect and other important data may be missing.
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