Near-Optimal Learning of Tree-Structured Distributions by Chow and Liu
From MaRDI portal
Publication:6110527
DOI10.1137/22m1489678arXiv2011.04144MaRDI QIDQ6110527
Vincent Y. F. Tan, Arnab Bhattacharyya, N. V. Vinodchandran, Eric Price, Sutanu Gayen
Publication date: 6 July 2023
Published in: SIAM Journal on Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2011.04144
Computational learning theory (68Q32) Information theory (general) (94A15) Randomized algorithms (68W20)
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Efficient distribution-free learning of probabilistic concepts
- Toward efficient agnostic learning
- The sample complexity of learning fixed-structure Bayesian networks
- An optimal approximation algorithm for Bayesian inference
- Maximum likelihood bounded tree-width Markov networks
- Minimax optimal conditional independence testing
- The minimax learning rates of normal and Ising undirected graphical models
- Learning a tree-structured Ising model in order to make predictions
- Convergence properties of functional estimates for discrete distributions
- 10.1162/153244301753344605
- Efficiently Learning Ising Models on Arbitrary Graphs
- On Testing Expansion in Bounded-Degree Graphs
- Graphical Models, Exponential Families, and Variational Inference
- A theory of the learnable
- Factor graphs and the sum-product algorithm
- Asymptotic Coupling and Its Applications in Information Theory
- Estimation of Entropy and Mutual Information
- Optimal Identity Testing with High Probability
- Testing Bayesian Networks
- Testing Ising Models
- Testing conditional independence of discrete distributions
- A Large-Deviation Analysis of the Maximum-Likelihood Learning of Markov Tree Structures
- Introduction to Property Testing
- Approximating discrete probability distributions with dependence trees
- Reconstruction of Markov Random Fields from Samples: Some Observations and Algorithms
- Near-Optimal Learning of Tree-Structured Distributions by Chow and Liu
This page was built for publication: Near-Optimal Learning of Tree-Structured Distributions by Chow and Liu