Statistics University of Wisconsin-Madison Madison / /
IndustryTerm
power-law degree distribution / k-means algorithm / spectral clustering algorithm / spectral clustering algorithms / canonical spectral clustering algorithm / neural information processing systems / empirical networks / sparse empirical networks / Social networks / spectral algorithms / empirical network / above algorithm / large sparse networks / graph algorithms / power law distribution / sparse network / spectral algorithm / /
Organization
Stochastic Blockmodel SBM / National Institute of Health / National Science Foundation / American Statistical Association / WARF / Degree-Corrected Stochastic Blockmodel Karl Rohe Department / University of Wisconsin / /
Person
Sara Fernandes-Taylor / Frank McSherry / Kamal M. Ali / Elizaveta Levina / Peter J Bickel / Aiyou Chen / Brian Karrer / Mary Radcliffe / Michael I Jordan / Chung / Amin Coja-Oghlan / John E Hopcroft / Michael W Mahoney / Andrew Y Ng / Anirban Dasgupta / Stephen A Vavasis / Arash A Amini / Jeffrey D. Scargle / Yair Weiss / Ashok N. Srivastava / Natalie Glance / Lada A Adamic / Peter H Sch / Tai Qin / /
PoliticalEvent
presidential election / /
Product
Uzi / /
ProvinceOrState
Wisconsin / South Carolina / /
PublishedMedium
Machine Learning / Journal of Machine Learning Research / Journal of the American Statistical Association / /
Regularized Spectral Clustering under the Degree-Corrected Stochastic Blockmodel Karl Rohe Department of Statistics University of Wisconsin-Madison