Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models
Author:
Affiliation:
1. MIT,Department of EECS,Cambridge,MA,USA
2. MIT,Department of Mathematics,Cambridge,MA,USA
Funder
NSF Graduate Fellowship
MIT-IBM Watson AI Lab and NSF CAREER
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9719594/9719683/09719784.pdf?arnumber=9719784
Reference38 articles.
1. Sparse logistic regression learns all discrete pairwise graphical models;wu;Advances in neural information processing systems,2019
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3. Phylogeny
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Cited by 4 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. A Unified Approach to Learning Ising Models: Beyond Independence and Bounded Width;Proceedings of the 56th Annual ACM Symposium on Theory of Computing;2024-06-10
2. Near-Optimal Learning of Tree-Structured Distributions by Chow and Liu;SIAM Journal on Computing;2023-06-15
3. Learning Polynomial Transformations via Generalized Tensor Decompositions;Proceedings of the 55th Annual ACM Symposium on Theory of Computing;2023-06-02
4. Active-LATHE: An Active Learning Algorithm for Boosting the Error Exponent for Learning Homogeneous Ising Trees;IEEE Transactions on Information Theory;2023-04
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