时间：2015年6月11日(星期四)下午15:00
地点：旗山校区理工楼601学术报告厅
主办：数学与计算机科学学院、数学研究中心
主讲：Harvard University（哈佛大学） Dr. Yi Li
报告摘要：Efficient processing of massive data sets has become increasingly important over the last two decades. The data streaming model, in particular, the turnstile streaming model, has attracted a lot of attention. In this model, an underlying vector x in R^n is presented as a long sequence of positive and negative updates to its coordinates. A randomized algorithm seeks to approximate a function f(x) with constant probability while only making a single pass over this sequence of updates and using a small amount of space. I shall give a brief introduction to the basic concepts and notions as well as typical approaches, then present the sparse recovery problem in greater detail (where f(x) returns the largest coordinates of x). In the end I shall discuss some future projects and directions.