On the Optimal Bounds for Noisy Computing
Author:
Affiliation:
1. University of California,Berkeley
2. University of British Columbia
3. University of California San Diego
Funder
Research and Development
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10206429/10206441/10206881.pdf?arnumber=10206881
Reference48 articles.
1. Maximum selection and ranking under noisy comparisons;falahatgar;Proceedings of the 34th International Conference on Machine Learning,2017
2. Probabilistic Logics and the Synthesis of Reliable Organisms From Unreliable Components
3. Active learning for top-k rank aggregation from noisy comparisons;mohajer;Proceedings of the 34th International Conference on Machine Learning - Volume 70,2017
4. Upper bound on the redundancy of self-correcting arrangements of unreliable functional elements;dobrushin;Problemy Peredachi Informatsii,1977
5. Active ranking from pairwise comparisons and when parametric assumptions do not help
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