A Correction of Pseudo Log-Likelihood Method
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Abstract (arXiv)
Pseudo log-likelihood is a type of maximum likelihood estimation (MLE) method used in various fields including contextual bandits, influence maximization of social networks, and causal bandits. However, in previous literature citepli2017provably, zhang2022online, xiong2022combinatorial, feng2023combinatorial1, feng2023combinatorial2, the log-likelihood function may not be bounded, which may result in the algorithm they proposed not well-defined. In this paper, we give a counterexample that the maximum pseudo log-likelihood estimation fails and then provide a solution to correct the algorithms in citepli2017provably, zhang2022online, xiong2022combinatorial, feng2023combinatorial1, feng2023combinatorial2.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 3 of its 6 references that are in the map. First posted on arXiv 26 Mar 2024.
Builds on
3 of 6 references.
References · 3
- 2022Combinatorial Causal Banditscited by 16
- 2022Combinatorial Pure Exploration of Causal Banditscited by 9
- 2023Combinatorial Causal Bandits without Graph Skeletoncited by 7
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Citing papers per year: 2026: 1.
1 paper.
- 2026Contextual Procurement Auctions with Bandit Learningcited by 0
- 2026Contextual Procurement Auctions with Bandit Learning7 Jul 2026