activity
20172021
most citedComputing Extremely Accurate Quantiles Using t-Digests

42 citations · 78 across the 5 of their papers we have counts for

collaborators

8 papers

cs.DS2021

Estimation from Partially Sampled Distributed Traces

Otmar Ertl

Sampling is often a necessary evil to reduce the processing and storage costs of distributed tracing. In this work, we describe a scalable and adaptive sampling approach that can p…

cs.DS2021

SetSketch: Filling the Gap between MinHash and HyperLogLog

Otmar Ertl

MinHash and HyperLogLog are sketching algorithms that have become indispensable for set summaries in big data applications. While HyperLogLog allows counting different elements wit…

cs.DS2019

ProbMinHash -- A Class of Locality-Sensitive Hash Algorithms for the (Probability) Jaccard Similarity

Otmar Ertl

The probability Jaccard similarity was recently proposed as a natural generalization of the Jaccard similarity to measure the proximity of sets whose elements are associated with r…

stat.CO201942 cited

Computing Extremely Accurate Quantiles Using t-Digests

Ted Dunning, Otmar Ertl

We present on-line algorithms for computing approximations of rank-based statistics that give high accuracy, particularly near the tails of a distribution, with very small sketches…

cs.DS2018

BagMinHash - Minwise Hashing Algorithm for Weighted Sets

Otmar Ertl

Minwise hashing has become a standard tool to calculate signatures which allow direct estimation of Jaccard similarities. While very efficient algorithms already exist for the unwe…

cs.DS20177 cited

New Cardinality Estimation Methods for HyperLogLog Sketches

Otmar Ertl

This work presents new cardinality estimation methods for data sets recorded by HyperLogLog sketches. A simple derivation of the original estimator was found, that also gives insig…