5 papers
Low-Rank Graphon Learning for Networks
Xinyuan Fan, Feiyan Ma, Chenlei Leng +1
Graphons offer a powerful framework for modeling large-scale networks, yet estimation remains challenging. We propose a novel approach that leverages a low-rank additive representa…
DAG-Math: Graph-of-Thought Guided Mathematical Reasoning in LLMs
Yuanhe Zhang, Ilja Kuzborskij, Jason D. Lee +2
Large Language Models (LLMs) demonstrate strong performance on mathematical problems when prompted with Chain-of-Thought (CoT), yet it remains unclear whether this success stems fr…
Regression Analysis of Reciprocity in Directed Networks
Rui Feng, Chenlei Leng
Reciprocity--the tendency of individuals to form mutual ties--is a fundamental structural feature of many directed networks. Despite its ubiquity, reciprocity remains insufficientl…
Causal Inference under Interference: Regression Adjustment and Optimality
Xinyuan Fan, Chenlei Leng, Weichi Wu
In randomized controlled trials without interference, regression adjustment is widely used to enhance the efficiency of treatment effect estimation. This paper extends this efficie…
Modelling Directed Networks with Reciprocity
Rui Feng, Chenlei Leng
Asymmetric relational data is increasingly prevalent across diverse fields, underscoring the need for directed network models to address the complex challenges posed by their uniqu…