2 July 2021 - 3-4pm UK time

Speaker: Kevin Lin (University of Pennsylvania)

Title: Time-varying stochastic block models, with application to understanding the dynamics of gene co-expression

Abstract - Single-cell data enables us to investigate how gene co-expression patterns change as cells develop across time. While this question is multifaceted, we focus on understanding the theory behind a particular subtask in this talk: clustering nodes across many undirected labeled graphs indexed by time, also known as multilayer networks. Specifically, we discuss two stochastic block model (SBM) settings: one where the true connectivities among the clusters change over time while the true nodes' cluster memberships are held fixed, and another where both the SBMs' true node memberships and cluster connectivities vary smoothly across time. Our estimator is based on averaging the appropriately-debiased squared adjacency matrices followed by spectral clustering, and we demonstrate how our theoretical results improve upon the existing regimes-of-consistency (in terms of clustering error) as well as the rates-of-convergence in the literature. These results demonstrate the interplay among the number of nodes and graphs, the graph sparsity, and the rate-of-change in true cluster memberships or cluster connectivities across layers. We then demonstrate how our estimator performs empirically on single-cell data. This is a joint work with Jing Lei.

To register your interest in accessing the StatScale Seminars, contact Dr Hyeyoung Maeng 


18 June 2021 - Runmin Wang (Southern Methodist University)

Dating the Break in High Dimensional Data


4 June 2021 -  Abolfazl Safikhani (University of Florida)

Multiple Change Point Detection in Reduced Rank High Dimensional Vector Autoregressive Models


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7th May 2021 - Lynna Chu (Iowa State University)

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19th June, 2020 - Martin Tveten (Dept. of Mathematics, University of Oslo)

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5th June, 2020 - Yudong Chen (University of Cambridge)

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