NeurIPS 2019
Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
Paper ID:5971
Title:Greedy Sampling for Approximate Clustering in the Presence of Outliers


		
The authors show that mild modifications to existing greedy iterative algorithms can make these robust to outliers. While the modifications are simple and looks incremental the reviewers feel that the analysis will be interesting to Neurips audience. The authors should cite the algorithms pointed out by the reviewers, since they are also based on successive sampling and can be thought of as adaptive methods. The experiments should include more comparisons as pointed out by the reviewers.