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Relational tables, where each row corresponds to an entity and each column corresponds to an attribute, have been the standard for tables in relational databases.
Language models are few-shot learners
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A simple guide to five normal forms in relational database theory
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Imagenet: A large-scale hierarchical image database. In 2009 IEEE conference on computer vision and pattern recognition . Ieee, 248–255
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. 2009 · 2009
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Query by output. In Proceedings of the 2009 ACM SIGMOD International Conference on Management of data . 535–548
Quoc Trung Tran, Chee-Yong Chan, and Srinivasan Parthasarathy. 2009 · 2009
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Spreadsheet data manipulation using examples
Sumit Gulwani, William R Harris, and Rishabh Singh. 2012 · 2012
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Machine learning: a probabilistic perspective
Kevin P Murphy. 2012 · 2012
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Automatically synthesizing sql queries from input-output examples. In 2013 28th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 224–234
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Glove: Global vectors for word representation. In Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP) . 1532–1543
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman. 2014 · 2014
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FlashRelate: extracting relational data from semi-structured spreadsheets using examples
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Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition . 770–778
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
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Enriching word vectors with subword information
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Foofah: Transforming data by example. In Proceedings of the 2017 ACM International Conference on Management of Data . 683–698
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Imagenet classification with deep convolutional neural networks
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Automatic differentiation in PyTorch
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Auto-join: Joining tables by leveraging transformations
Erkang Zhu, Yeye He, and Surajit Chaudhuri. 2017 · 2017
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Navigating the data lake with datamaran: Automatically extracting structure from log datasets. In Proceedings of the 2018 International Conference on Management of Data . 943–958
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Transform-data-by-example (TDE) an extensible search engine for data transformations
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Cited alongside, same era.
Incorporating data context to cost-effectively automate end-to-end data wrangling
Martin Koehler, Edward Abel, Alex Bogatu, Cristina Civili, Lacramioara Mazilu, Nikolaos Konstantinou, Alvaro AA Fernandes, John Keane, Leonid Libkin, and Norman W Paton. 2019 · 2019
Cited alongside, same era.
A survey on image data augmentation for deep learning
Connor Shorten and Taghi M Khoshgoftaar. 2019 · 2019
Example Excel forum question to relationalize tables: Data restructuring using Excel (Retrieved in 02/2023)
[n.d.]a · 2023
Closest in time.
Example Excel forum question to relationalize tables: Pivot chart 4 columns (Retrieved in 02/2023)
[n.d.]b · 2023
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Example Excel forum question to relationalize tables: Pivot table issue. (Retrieved in 02/2023)
[n.d.]c · 2023
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Example Excel forum question to relationalize tables: Transpose data for analysis (Retrieved in 02/2023)
[n.d.]d · 2023
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Example StackOverflow forum question to relationalize tables: Melt index (Retrieved in 02/2023)
[n.d.]a · 2023
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Example StackOverflow forum question to relationalize tables: Melt multiple columns (Retrieved in 02/2023)
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Cited alongside, same era.
TaPas: Weakly supervised table parsing via pre-training
Jonathan Herzig, Paweł Krzysztof Nowak, Thomas Müller, Francesco Piccinno, and Julian Martin Eisenschlos. 2020 · 2020
Cited alongside, same era.
Auto-transform: learning-to-transform by patterns
Zhongjun Jin, Yeye He, and Surajit Chauduri. 2020 · 2020
Cited alongside, same era.
Keita Takenouchi, Takashi Ishio, Joji Okada, and Yuji Sakata. 2020 · 2020
Cited alongside, same era.
Auto-suggest: Learning-to-recommend data preparation steps using data science notebooks. In Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data . 1539–1554
Cong Yan and Yeye He. 2020 · 2020
Cited alongside, same era.
TaBERT: Pretraining for joint understanding of textual and tabular data
Pengcheng Yin, Graham Neubig, Wen-tau Yih, and Sebastian Riedel. 2020 · 2020
Cited alongside, same era.
A survey of convolutional neural networks: analysis, applications, and prospects
Zewen Li, Fan Liu, Wenjie Yang, Shouheng Peng, and Jun Zhou. 2021 · 2021
Cited alongside, same era.
Auto-pipeline: synthesizing complex data pipelines by-target using reinforcement learning and search
Junwen Yang, Yeye He, and Surajit Chaudhuri. 2021 · 2021
Cited alongside, same era.
[n.d.]b · 2023
Closest in time.
Example StackOverflow forum question to relationalize tables: Melt with multiple value vars (Retrieved in 02/2023)
[n.d.]c · 2023
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Example StackOverflow forum question to relationalize tables: Reshape wide-to-long in Pandas (Retrieved in 02/2023)
[n.d.]d · 2023
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Pandas operator: Explode. (Retrieved in 02/2023)
[n.d.]a · 2023
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Pandas operator: FFill. (Retrieved in 02/2023)
[n.d.]b · 2023
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Pandas operator: Melt. (Retrieved in 02/2023)
[n.d.]c · 2023
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Pandas operator: Pivot. (Retrieved in 02/2023)
[n.d.]d · 2023
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Pandas operator: Stack. (Retrieved in 02/2023)
[n.d.]e · 2023
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Pandas operator: Transpose. (Retrieved in 02/2023)
[n.d.]f · 2023
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Pandas operator: Wide-to-long. (Retrieved in 02/2023)
[n.d.]g · 2023
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R operator: pivot-longer, which is similar to Wide-to-long. (Retrieved in 02/2023)
[n.d.]h · 2023
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Trifacta: Standardize Using Patterns. (Retrieved in 07/2023)
[n.d.] · 2023
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Auto-BI: Automatically Build BI-Models Leveraging Local Join Prediction and Global Schema Graph
Yiming Lin, Yeye He, and Surajit Chaudhuri. 2023 · 2023
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