activity
20172022
most citedStreaming Robust Submodular Maximization: A Partitioned Thresholding Approach

14 citations · 32 across the 6 of their papers we have counts for

collaborators

10 papers

cs.LG20223 cited

Near-Optimal Correlation Clustering with Privacy

Vincent Cohen-Addad, Chenglin Fan, Silvio Lattanzi +4

Correlation clustering is a central problem in unsupervised learning, with applications spanning community detection, duplicate detection, automated labelling and many more. In the…

cs.DS2021

Online Edge Coloring via Tree Recurrences and Correlation Decay

Janardhan Kulkarni, Yang P. Liu, Ashwin Sah +2

We give an online algorithm that with high probability computes a edge coloring on a graph with maximum degree under online…

cs.DS20213 cited

Correlation Clustering in Constant Many Parallel Rounds

Vincent Cohen-Addad, Silvio Lattanzi, Slobodan Mitrović +3

Correlation clustering is a central topic in unsupervised learning, with many applications in ML and data mining. In correlation clustering, one receives as input a signed graph an…

cs.DS2021

On the Hardness of Scheduling With Non-Uniform Communication Delays

Sami Davies, Janardhan Kulkarni, Thomas Rothvoss +3

In the scheduling with non-uniform communication delay problem, the input is a set of jobs with precedence constraints. Associated with every precedence constraint between a pair o…

cs.LG2020

Fairness in Streaming Submodular Maximization: Algorithms and Hardness

Marwa El Halabi, Slobodan Mitrović, Ashkan Norouzi-Fard +2

Submodular maximization has become established as the method of choice for the task of selecting representative and diverse summaries of data. However, if datapoints have sensitive…

cs.LG2020

Efficient Algorithms for Device Placement of DNN Graph Operators

Jakub Tarnawski, Amar Phanishayee, Nikhil R. Devanur +2

Modern machine learning workloads use large models, with complex structures, that are very expensive to execute. The devices that execute complex models are becoming increasingly h…