报告人：晏挺（教授，华中师范大学）
报告题目：Inference using a differential private bi-degree sequence of directed graphs
报告摘要：In this talk, we release the bi-degree sequence of a directed graph using a discrete Laplace mechanism and propose an efficient algorithm for finding a maximum likelihood estimate of the bi-degree sequence, which is equivalent to projecting the noisy bi-degree sequence on the set of all graphical bi-degree sequences with the $L_1$ distance. Along the way, our algorithm also outputs a synthetic directed graph. By using the outputs, we present a differentially private estimator of the parameter in the $p_0$ model. We show that the estimator is asymptotically consistent and normally distributed, whose rate of convergence is the same as the non-private estimator. Numerical studies demonstrate our theoretical findings.
报告时间：2018年3月22日（星期四）下午4:00-5:00
报告地点：科技楼南楼702
