Minimax Rates in Network Analysis: Graphon Estimation, Community Detection and Hypothesis Testing
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Abstract (arXiv)
This paper surveys some recent developments in fundamental limits and optimal algorithms for network analysis. We focus on minimax optimal rates in three fundamental problems of network analysis: graphon estimation, community detection, and hypothesis testing. For each problem, we review state-of-the-art results in the literature followed by general principles behind the optimal procedures that lead to minimax estimation and testing. This allows us to connect problems in network analysis to other statistical inference problems from a general perspective.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Nov 2018.
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Citing papers per year: 2022: 1; 2023: 4; 2024: 3.
8 papers.
- 2023Conformal Prediction for Network-Assisted Regressioncited by 14
- 2023Computational Lower Bounds for Graphon Estimation via Low-degree Polynomialscited by 6
- 2023Graphon Estimation in bipartite graphs with observable edge labels and unobservable node labelscited by 2
- 2022Modeling and Correcting Bias in Sequential Evaluationcited by 0
- 2023Fitting Low-rank Models on Egocentrically Sampled Partial Networkscited by 0
- 2024A Deep Learning Method for Optimal Investment Under Relative Performance Criteria Among Heterogeneous Agentscited by 0
- 2024Estimating Dyadic Treatment Effects with Unknown Confounderscited by 0
- 2024Network-based Neighborhood regressioncited by 0
- 2024Network-based Neighborhood regression4 Jul 2024
- 2024Estimating Dyadic Treatment Effects with Unknown Confounders26 May 2024
- 2024A Deep Learning Method for Optimal Investment Under Relative Performance Criteria Among Heterogeneous Agents12 Feb 2024
- 2023Computational Lower Bounds for Graphon Estimation via Low-degree Polynomials30 Aug 2023
- 2023Graphon Estimation in bipartite graphs with observable edge labels and unobservable node labels7 Apr 2023
- 2023Fitting Low-rank Models on Egocentrically Sampled Partial Networks9 Mar 2023
- 2023Conformal Prediction for Network-Assisted Regression20 Feb 2023
- 2022Modeling and Correcting Bias in Sequential Evaluation3 May 2022