Properly learning monotone functions via local correction
Author:
Affiliation:
1. CSAIL MIT,Cambridge,USA
Funder
Google
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9996589/9996592/09996614.pdf?arnumber=9996614
Reference54 articles.
1. Lower Bounds for Local Monotonicity Reconstruction from Transitive-Closure Spanners
2. Domain Reduction for Monotonicity Testing: A o(d) Tester for Boolean Functions in d-Dimensions
3. Properly learning decision trees in almost polynomial time
4. The randomized local computation complexity of the Lovász local lemma;brandt;CoRR,2021
5. Learnability of DNF with representation-specific queries
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Dynamic (1+ϵ)-Approximate Matching Size in Truly Sublinear Update Time;2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS);2023-11-06
2. Agnostic proper learning of monotone functions: beyond the black-box correction barrier;2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS);2023-11-06
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