Learning of leader-follower graph from time-correlated big data streams with missing entries
Nowadays we are collecting high-dimensional and large data streams, where many dimensions can be expressing basically the same information on the underlying process of interest. This redundancy is apparent, for example, if we observe mass media news outputs through time. Here, even the discovery of the leader-follower structure of the news streams is valuable information.
I will be presenting very recent work approaching the leader-follower problem with missing entries, using scalable and accurate algorithms for big data streams.