Our present work offers an empirical tool for the theoretician: a software package that generates benchmark graphs with user controlled parame- ters and ...
In this thesis, two problems in social networks will be studied. In the first part of the thesis, we focus on community recovery problems for social ...
Benchmarking recovery theorems for the DC-SBM. Y Wan, M Meila. ISAIM, 2016. 5, 2016. Topics in Graph Clustering. Y Wan. 2, 2017. Measuring the Robustness of ...
Apr 25, 2024 · Benchmarking recovery theorems for the DC-SBM. ISAIM 2016. [c2]. view. electronic edition @ neurips.cc (open access); electronic edition @ nips ...
Benchmarking recovery theorems for the DC-SBM.. Y Wan, M Meila. ISAIM, 2016 ... Benchmarking recovery theorems for the degree corrected stochastic block model.
Benchmarking recovery theorems for the DC-SBM. Y Wan, M Meila. ISAIM, 2016. 5, 2016. Topics in Graph Clustering. Y Wan. 2, 2017. Measuring the Robustness of ...
TL;DR: This paper explores experimentally the limits of the current theory of the DC-SBM by generating benchmark cases, for which recovery is possible, and with ...
Benchmarking recovery theorems for the DC-SBM Yali Wan and Marina Meila; Partial Collective Matrix Factorization and its PAC Bound Chao Lan, Xiaoli Li, Yujie ...
Yali Wan and Marina Meila. Benchmarking recovery theorems for the DC-SBM James Atwood and Don Towsley. Search-Convolutional Neural Networks Guilllermo ...
Clustering graphs under the Stochastic Block Model (SBM) and extensions are well studied. Guarantees of correctness exist under the assumption that the data.