activity
20162021
most citedBoostClean: Automated Error Detection and Repair for Machine Learning

58 citations · 178 across the 12 of their papers we have counts for

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11 papers · 1 filter

cs.DB20212 cited

Version Reconciliation for Collaborative Databases

Nalin Ranjan, Zechao Shang, Aaron J. Elmore +1

We propose MindPalace, a prototype of a versioned database for efficient collaborative data management. MindPalace supports offline collaboration, where users work independently wi…

cs.DB20211 cited

Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing

Xi Liang, Stavros Sintos, Zechao Shang +1

Sample-based approximate query processing (AQP) suffers from many pitfalls such as the inability to answer very selective queries and unreliable confidence intervals when sample si…

cs.DB2021

CIAO: An Optimization Framework for Client-Assisted Data Loading

Cong Ding, Dixin Tang, Xi Liang +2

Data loading has been one of the most common performance bottlenecks for many big data applications, especially when they are running on inefficient human-readable formats, such as…

cs.DB20202 cited

The Data Station: Combining Data, Compute, and Market Forces

Raul Castro Fernandez, Kyle Chard, Ben Blaiszik +7

This paper introduces Data Stations, a new data architecture that we are designing to tackle some of the most challenging data problems that we face today: access to sensitive data…

cs.DB2020

Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints

Xi Liang, Zechao Shang, Aaron J. Elmore +2

Today, data analysts largely rely on intuition to determine whether missing or withheld rows of a dataset significantly affect their analyses. We propose a framework that can produ…

cs.DB201934 cited

AlphaClean: Automatic Generation of Data Cleaning Pipelines

Sanjay Krishnan, Eugene Wu

The analyst effort in data cleaning is gradually shifting away from the design of hand-written scripts to building and tuning complex pipelines of automated data cleaning libraries…