Machine Learning with Small Data for User Modeling of Watershed Stakeholders Engaged in Interactive Optimization-Reference-Cited by-同舟云学术

Machine Learning with Small Data for User Modeling of Watershed Stakeholders Engaged in Interactive Optimization

Published:2018 Issue: Volume: Page:
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Container-title:Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence - CSAI '18
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Author:

Hoblitzell Andrew¹,Babbar-Sebens Meghna²,Mukhopadhyay Snehasis¹

Affiliation:

1. Department of Computer Science, IUPUI, Indianapolis, IN

2. School of Civil and Construction Engineering, Oregon State University, Corvallis, OR

Publisher

ACM Press

Reference45 articles.

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2. M. Banko, and E. Brill, Scaling to very very large corpora for natural language disambiguation, in Proc. 39th Ann. meeting on association for computational linguistics, 2001, pp. 26--33.

3. V.N. Gudivada, R.A. Baeza-Yates, and V.V. Raghavan, Big Data: Promises and Problems, IEEE Computer, vol. 48, no. 3, pp. 20--23, 2015.

4. S. Ben-David, J. Blitzer, K. Crammer, and F. Pereira, Analysis of Representations for Domain Adaptation, Proc. 20th Ann. Conf. Neural Information Processing Systems, 2007, pp. 137--144.

5. T.M. Ha and H. Bunke, Off-Line Handwritten Numeral Recognition by Perturbation Method, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 5, pp. 535--539, May, 1997.

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