Search Results for author: Emanuel Zgraggen

Found 4 papers, 4 papers with code

ARDA: Automatic Relational Data Augmentation for Machine Learning

1 code implementation21 Mar 2020 Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen, Raul Castro Fernandez, Tim Kraska, David Karger

Our system has two distinct components: (1) a framework to search and join data with the input data, based on various attributes of the input, and (2) an efficient feature selection algorithm that prunes out noisy or irrelevant features from the resulting join.

BIG-bench Machine Learning Data Augmentation +2

Sherlock: A Deep Learning Approach to Semantic Data Type Detection

2 code implementations25 May 2019 Madelon Hulsebos, Kevin Hu, Michiel Bakker, Emanuel Zgraggen, Arvind Satyanarayan, Tim Kraska, Çağatay Demiralp, César Hidalgo

Correctly detecting the semantic type of data columns is crucial for data science tasks such as automated data cleaning, schema matching, and data discovery.

Column Type Annotation Vocal Bursts Type Prediction +1

VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository

1 code implementation12 May 2019 Kevin Hu, Neil Gaikwad, Michiel Bakker, Madelon Hulsebos, Emanuel Zgraggen, César Hidalgo, Tim Kraska, Guoliang Li, Arvind Satyanarayan, Çağatay Demiralp

Researchers currently rely on ad hoc datasets to train automated visualization tools and evaluate the effectiveness of visualization designs.


IDEBench: A Benchmark for Interactive Data Exploration

1 code implementation7 Apr 2018 Philipp Eichmann, Carsten Binnig, Tim Kraska, Emanuel Zgraggen

Existing benchmarks for analytical database systems such as TPC-DS and TPC-H are designed for static reporting scenarios.


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