2017-06-01
A survey of quantum learning theory
Publication
Publication
Computational Complexity Guest Column , Volume 48 - Issue 2 p. 41- 67
This paper surveys quantum learning theory: the theoretical aspects of machine learning using quantum computers. We describe the main results known for three models of learn- ing: exact learning from membership queries, and Probably Approximately Correct (PAC) and agnostic learning from classical or quantum examples.
| Additional Metadata | |
|---|---|
| , , | |
| doi.org/10.1145/3106700.3106710 | |
| Computational Complexity Guest Column | |
| Organisation | Algorithms and Complexity |
|
Arunachalam, S., & de Wolf, R. (2017). A survey of quantum learning theory. ACM SIGACT News, 48(2), 41–67. doi:10.1145/3106700.3106710 |
|
