1.6k citations · 3.9k across the 64 of their papers we have counts for
Showing 2016Show all
2 papers · 1 filter
stat.ML2016
Graphons, mergeons, and so on!
Justin Eldridge, Mikhail Belkin, Yusu Wang
In this work we develop a theory of hierarchical clustering for graphs. Our modeling assumption is that graphs are sampled from a graphon, which is a powerful and general model for…
cs.LG2016★ 56 cited
Learning Privately from Multiparty Data
Jihun Hamm, Paul Cao, Mikhail Belkin
Learning a classifier from private data collected by multiple parties is an important problem that has many potential applications. How can we build an accurate and differentially…