Computer Science/Discrete Mathematics Seminar II

Consensus clustering is the problem of aggregating a list of clusterings of ground data into one clustering. I will present new approximation algorithms for this problem, building on techniques used for ranking problems (described in my previous talk). I will then discuss hierarchical clustering, a special type of metric embedding problem relevant to phylogeny, and will present new algorithms. I will repeat all relevant definitions and results from my previous talk. Based on work with Moses Charikar and Alantha Newman.