arXiv:1811.06055
Minimax Rates in Network Analysis: Graphon Estimation, Community Detection and Hypothesis Testing
원문 초록
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.
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Computational Lower Bounds for Graphon Estimation via Low-degree Polynomials
Learning to Collaborate Over Graphs: A Selective Federated Multi-Task Learning Approach
Breaking the Batch Barrier (B3) of Contrastive Learning via Smart Batch Mining
Advancing Community Detection with Graph Convolutional Neural Networks: Bridging Topological and Attributive Cohesion
Community and hyperedge inference in multiple hypergraphs
Adaptive Long-term Embedding with Denoising and Augmentation for Recommendation
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