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Data science requires time-consuming iterative manual activities.
Some methods for classification and analysis of multivariate observations
MacQueen, J · 1967
Earlier work this paper cites.
How progressive visualizations affect exploratory analysis
Zgraggen, E., Galakatos, A., Crotty, A., Fekete, J.-D., and Kraska, T · 1987
Earlier work this paper cites.
Support-vector networks
Cortes, C., and Vapnik, V · 1995
Earlier work this paper cites.
Online aggregation
Hellerstein, J. M., Haas, P. J., and Wang, H. J · 1997
Earlier work this paper cites.
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Hellerstein, J. M., Avnur, R., Chou, A., Hidber, C., Olston, C., Raman, V., Roth, T., and Haas, P. J · 1999
Earlier work this paper cites.
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Joseph, M., Avnur, R., Olston, C., Roth, T., Haas, P. J., Hellerstein, J. M., Chou, A., Hidber, C., and Raman, V · 1999
Earlier work this paper cites.
Scalable Spreadsheets for Interactive Data Analysis
Raman, V., Chou, A., and Hellerstein, J. M · 1999
Earlier work this paper cites.
Online Dynamic Reordering for Interactive Data Processing
Raman, V., Hellerstein, J. M., and Raman, B · 1999
Earlier work this paper cites.
Random forests
Breiman, L · 2001
Earlier work this paper cites.
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Collins, L. M., Schafer, J. L., and Kam, C.-M · 2001
Earlier work this paper cites.
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Earlier work this paper cites.
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Williams, M., and Munzner, T · 2004
Earlier work this paper cites.
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Keim, D., Andrienko, G., Fekete, J. D., Görg, C., Kohlhammer, J., and Melançon, G · 2008
Earlier work this paper cites.
MOA: massive online analysis
Bifet, A., Holmes, G., Kirkby, R., and Pfahringer, B · 2010
Earlier work this paper cites.
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Pan, S. J., Yang, Q., et al · 2010
Earlier work this paper cites.
D 3 data-driven documents
Bostock, M., Ogievetsky, V., and Heer, J · 2011
Earlier work this paper cites.
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Earlier work this paper cites.
Wrangler: Interactive visual specification of data transformation scripts
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Earlier work this paper cites.
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Earlier work this paper cites.
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Fisher, D., Popov, I., Drucker, S. M., and Schraefel, M. C · 2012
Earlier work this paper cites.
Adaptive indexing in modern database kernels
Idreos, S., Manegold, S., and Graefe, G · 2012
Earlier work this paper cites.
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Earlier work this paper cites.
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Agarwal, S., Mozafari, B., Panda, A., Milner, H., Madden, S., and Stoica, I · 2013
Earlier work this paper cites.
Big Data Exploration
Idreos, S · 2013
Earlier work this paper cites.
Kdd pipeline
Kriegel, H.-P., and Schubert, M · 2013
Earlier work this paper cites.
Error Bars Considered Harmful: Exploring Alternate Encodings for Mean and Error
Correll, M., and Gleicher, M · 2014
Earlier work this paper cites.
Learning an invariant speech representation, 2014
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Earlier work this paper cites.
A survey on concept drift adaptation
Gama, J., Žliobaitė, I., Bifet, A., Pechenizkiy, M., and Bouchachia, A · 2014
Earlier work this paper cites.
Distributed and interactive cube exploration
Kamat, N., Jayachandran, P., Tunga, K., and Nandi, A · 2014
Earlier work this paper cites.
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Le, V., and Gulwani, S · 2014
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Cited alongside, same era.
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Cheng, Y., Zhao, W., and Rusu, F · 2017
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Optimal transport for domain adaptation
Courty, N., Flamary, R., Tuia, D., and Rakotomamonjy, A · 2017
Later among the works it cites.
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Dursun, K., Binnig, C., Cetintemel, U., and Kraska, T · 2017
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Feurer, M., Klein, A., Eggensperger, K., Springenberg, J. T., Blum, M., and Hutter, F · 2015
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