Accession Number:



Teaching Machines to Classify from Natural Language Interactions

Descriptive Note:

[Technical Report, Doctoral Thesis]

Corporate Author:

Carnegie Mellon University

Personal Author(s):

Report Date:


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Humans routinely learn new concepts using natural language communications, even in scenarios with limited or no labeled examples. For example, a human can learn the concept of a phishing email from natural language explanations such as phishing emails often request your bank account number. On the other hand, purely inductive learning systems typically require a large collection of labeled data for learning such a concept. We believe that advances in Computational Linguistics and the growing ubiquity of computing devices together can enable people to teach computers classification tasks using natural language interactions.

Subject Categories:

  • Linguistics

Distribution Statement:

[A, Approved For Public Release]