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20172024
most citedStochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error

8 citations · 21 across the 9 of their papers we have counts for

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stat.ML2017★ 6 cited

An Efficient Pseudo-likelihood Method for Sparse Binary Pairwise Markov Network Estimation

Sinong Geng, Zhaobin Kuang, David Page

The pseudo-likelihood method is one of the most popular algorithms for learning sparse binary pairwise Markov networks. In this paper, we formulate the regularized pseudo-lik…