2 citations · 6 across the 6 of their papers we have counts for
5 papers
Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees
Nicholas Schiefer, Justin Y. Chen, Piotr Indyk +3
An -approximate quantile sketch over a stream of inputs approximates the rank of any query point - that is, the number of input points less than - up to an…
Streaming Algorithms for Support-Aware Histograms
Justin Y. Chen, Piotr Indyk, Tal Wagner
Histograms, i.e., piece-wise constant approximations, are a popular tool used to represent data distributions. Traditionally, the difference between the histogram and the underlyin…
Near-Optimal (Euclidean) Metric Compression
Piotr Indyk, Tal Wagner
The metric sketching problem is defined as follows. Given a metric on points, and , we wish to produce a small size data structure (sketch) that, given any pair of point i…
Rapid Sampling for Visualizations with Ordering Guarantees
Albert Kim, Eric Blais, Aditya Parameswaran +3
Visualizations are frequently used as a means to understand trends and gather insights from datasets, but often take a long time to generate. In this paper, we focus on the problem…
Approximation Algorithms for Model-Based Compressive Sensing
Chinmay Hegde, Piotr Indyk, Ludwig Schmidt
Compressive Sensing (CS) stipulates that a sparse signal can be recovered from a small number of linear measurements, and that this recovery can be performed efficiently in polynom…