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DTSTART;TZID=America/Toronto:20200910T160000
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URL:/statistics-and-actuarial-science/events/department
 -seminar-emma-jingfei-zhang-miami-university
SUMMARY:Department seminar by Emma Jingfei Zhang\, Miami University
CLASS:PUBLIC
DESCRIPTION:Summary \n\nNETWORK RESPONSE REGRESSION FOR MODELING POPULATION
  OF NETWORKS WITH\nCOVARIATES\n\n-------------------------\n\nMultiple-net
 work data are fast emerging in recent years\, where a\nseparate network ov
 er a common set of nodes is measured for each\nindividual subject\, along 
 with rich subject covariates information.\nExisting network analysis metho
 ds have primarily focused on modeling a\nsingle network\, and are not dire
 ctly applicable to multiple networks\nwith subject covariates.\n\nIn this 
 talk\, we present a new network response regression model\,\nwhere the obs
 erved networks are treated as matrix-valued responses\,\nand the individua
 l covariates as predictors. The new model\ncharacterizes the population-le
 vel connectivity pattern through a\nlow-rank intercept matrix\, and the pa
 rsimonious effects of subject\ncovariates on the network through a sparse 
 slope tensor. We formulate\nthe parameter estimation as a non-convex optim
 ization problem\, and\ndevelop an efficient alternating gradient descent a
 lgorithm. We\nestablish the non-asymptotic error bound for the actual esti
 mator from\nour optimization algorithm. Built upon this error bound\, we d
 erive the\nstrong consistency for network community recovery\, as well as 
 the edge\nselection consistency. We demonstrate the efficacy of our method
 \nthrough intensive simulations and two brain connectivity studies.\n\nJoi
 n Zoom Meeting\n[https://zoom.us/j/8442836948?pwd=MVdCUFFCbVFuSzduQjhDQnNN
 Z3J1QT09]\n\nMeeting ID: 844 283 6948\nPasscode: 318995\n 
DTSTAMP:20250708T200657Z
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