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Abstract: This paper studies fundamental questions in computational learning theory from a quantum computation perspective. We consider quantum versions of two well-studied classical learning models: Angluin's model of exact learning from membership queries and Valiant's Probably Approximately Correct (PAC) model of learning from random examples. We give positive and negative results for quantum versus classical learnability. For each of the two learning models described above, we show that any concept... (Update)
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BibTeX entry: (Update)
R. A. Servedio and S. J. Gortler, "Quantum versus classical learnability", in Proceedings of the 16th Annual IEEE Conference on Computational Complexity, Chicago, IL, 18--21 June 2001. http://citeseer.ist.psu.edu/article/servedio00quantum.html More
@inproceedings{ servedio01quantum,
author = "Servedio and Gortler",
title = "Quantum versus Classical Learnability",
booktitle = "{SCT}: Annual Conference on Structure in Complexity Theory",
year = "2001",
url = "citeseer.ist.psu.edu/article/servedio00quantum.html" }
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