Rank aggregation is a well studied algorithmic problem where, given a set of input preference lists over a set of items, the objective is to compute a single ranking that best summarizes the individual lists. The problem has numerous applications, e.g., in social choice, recommendation systems, and information retrieval. In this talk we tackle this problem in the dynamic setting, and present a practically efficient 2-approximation algorithm with near linear update time for the problem. Based on joint work with Alireza Zarei and Morteza Alimi.

Zoom room information:
https://us06web.zoom.us/j/84906984159?pwd=BCWaIbXBuku3A5I84zNg9mHFxVZjXD.1
Meeting ID: 849 0698 4159
Passcode: 362880