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Probabilistic Data Structures for Web Analytics and Data Mining – Highly  Scalable Blog
Probabilistic Data Structures for Web Analytics and Data Mining – Highly Scalable Blog

A Survey on Advancing the DBMS Query Optimizer: Cardinality Estimation,  Cost Model, and Plan Enumeration | SpringerLink
A Survey on Advancing the DBMS Query Optimizer: Cardinality Estimation, Cost Model, and Plan Enumeration | SpringerLink

Data Streams
Data Streams

Augmented Sketch | Proceedings of the 2016 International Conference on  Management of Data
Augmented Sketch | Proceedings of the 2016 International Conference on Management of Data

M $$^2$$ M: A General Method to Perform Various Data Analysis Tasks from a  Differentially Private Sketch | SpringerLink
M $$^2$$ M: A General Method to Perform Various Data Analysis Tasks from a Differentially Private Sketch | SpringerLink

Mathematics | Free Full-Text | Selectivity Estimation of Inequality Joins  in Databases
Mathematics | Free Full-Text | Selectivity Estimation of Inequality Joins in Databases

Electronics | Free Full-Text | FO-Sketch: A Fast Oblivious Sketch for  Secure Network Measurement Service in the Cloud
Electronics | Free Full-Text | FO-Sketch: A Fast Oblivious Sketch for Secure Network Measurement Service in the Cloud

Stream [READ] Synopses for Massive Data: Samples, Histograms, Wavelets from  AshleyJones | Listen online for free on SoundCloud
Stream [READ] Synopses for Massive Data: Samples, Histograms, Wavelets from AshleyJones | Listen online for free on SoundCloud

Data Sketching | September 2017 | Communications of the ACM
Data Sketching | September 2017 | Communications of the ACM

Streaming analytics | 1st Europe Summer School: Data Science
Streaming analytics | 1st Europe Summer School: Data Science

Synopses for Massive Data: Samples, Histograms, Wavelets, Sketches (Bog,  Paperback / softback, Engelsk)
Synopses for Massive Data: Samples, Histograms, Wavelets, Sketches (Bog, Paperback / softback, Engelsk)

Amazon.com: Synopses for Massive Data: Samples, Histograms, Wavelets,  Sketches (Foundations and Trends(r) in Databases): 9781601985163: Cormode,  Graham, Garofalakis, Minos, Haas, Peter J.: Books
Amazon.com: Synopses for Massive Data: Samples, Histograms, Wavelets, Sketches (Foundations and Trends(r) in Databases): 9781601985163: Cormode, Graham, Garofalakis, Minos, Haas, Peter J.: Books

PDF] Correlation Sketches for Approximate Join-Correlation Queries |  Semantic Scholar
PDF] Correlation Sketches for Approximate Join-Correlation Queries | Semantic Scholar

PDF) In the Land of Data Streams where Synopses are Missing, the One  Framework to Bring Them All
PDF) In the Land of Data Streams where Synopses are Missing, the One Framework to Bring Them All

Comparing Synopsis Techniques for Approximate Spatial Data Analysis
Comparing Synopsis Techniques for Approximate Spatial Data Analysis

Data Synopses Generator V1 Work Package 6 Task 6.1 Deliverable 6.1
Data Synopses Generator V1 Work Package 6 Task 6.1 Deliverable 6.1

Variance Reduction in Frequency Estimators via Control Variates Method
Variance Reduction in Frequency Estimators via Control Variates Method

Amazon.com: Synopses for Massive Data: Samples, Histograms, Wavelets,  Sketches (Foundations and Trends(r) in Databases): 9781601985163: Cormode,  Graham, Garofalakis, Minos, Haas, Peter J.: Books
Amazon.com: Synopses for Massive Data: Samples, Histograms, Wavelets, Sketches (Foundations and Trends(r) in Databases): 9781601985163: Cormode, Graham, Garofalakis, Minos, Haas, Peter J.: Books

arXiv:2207.06596v1 [cs.DS] 14 Jul 2022
arXiv:2207.06596v1 [cs.DS] 14 Jul 2022

σ(S 3 ([ı..j])) versus LB =0 /(b − t) for b = 100,t = 50, b ı..j = 50... |  Download Scientific Diagram
σ(S 3 ([ı..j])) versus LB =0 /(b − t) for b = 100,t = 50, b ı..j = 50... | Download Scientific Diagram

Synopses over Streaming Data at Apache Flink | Semantic Scholar
Synopses over Streaming Data at Apache Flink | Semantic Scholar

Building Wavelet Histograms on Large Data in MapReduce
Building Wavelet Histograms on Large Data in MapReduce

In the Land of Data Streams where Synopses are Missing, One Framework to  Bring Them All
In the Land of Data Streams where Synopses are Missing, One Framework to Bring Them All