10 citations · 18 across the 6 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.DC2018
Submodular Optimization in the MapReduce Model
Paul Liu, Jan Vondrak
Submodular optimization has received significant attention in both practice and theory, as a wide array of problems in machine learning, auction theory, and combinatorial optimizat…
cs.SI2018★ 3 cited
A sampling framework for counting temporal motifs
Paul Liu, Austin Benson, Moses Charikar
Pattern counting in graphs is fundamental to network science tasks, and there are many scalable methods for approximating counts of small patterns, often called motifs, in large gr…
cs.DS2018★ 4 cited
Greedy and Local Ratio Algorithms in the MapReduce Model
Nicholas J. A. Harvey, Christopher Liaw, Paul Liu
MapReduce has become the de facto standard model for designing distributed algorithms to process big data on a cluster. There has been considerable research on designing efficient…