Legislative prediction with dual uncertainty minimization from heterogeneous information: Legislative Prediction with Dual Uncertainty Minimization

Cheng, Yu; Agrawal, Ankit; Liu, Huan; Choudhary, Alok

doi:10.1002/sam.11309

Title: Legislative prediction with dual uncertainty minimization from heterogeneous information: Legislative Prediction with Dual Uncertainty Minimization

Journal Article · Thu Apr 21 00:00:00 EDT 2016 · Statistical Analysis and Data Mining

DOI:https://doi.org/10.1002/sam.11309· OSTI ID:1533232

Cheng, Yu ^[1]; Agrawal, Ankit ^[2]; Liu, Huan ^[3]; Choudhary, Alok ^[2]

IBM T.J. Watson Center of Computational Healthcare Research Center, Yorktown Heights NY 10598 USA
EECS Department, Northwestern University, Evanston IL 60208 USA
Computer Science and Engineering, Arizona State University, Tempe AZ 85281 USA

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Research Organization:: Northwestern Univ., Evanston, IL (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

DOE Contract Number:: SC0007456; SC0014330

OSTI ID:: 1533232

Journal Information:: Statistical Analysis and Data Mining, Vol. 10, Issue 2; ISSN 1932-1864

Publisher:: Wiley

Country of Publication:: United States

Language:: English

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Patterns of Congressional Voting Poole, Keith T.; Rosenthal, Howard American Journal of Political Science, Vol. 35, Issue 1 https://doi.org/10.2307/2111445	journal	February 1991
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On Information and Sufficiency Kullback, S.; Leibler, R. A. The Annals of Mathematical Statistics, Vol. 22, Issue 1 https://doi.org/10.1214/aoms/1177729694	journal	March 1951
Nonlinear Dimensionality Reduction by Locally Linear Embedding Roweis, S. T. Science, Vol. 290, Issue 5500 https://doi.org/10.1126/science.290.5500.2323	journal	December 2000
Score normalization in multimodal biometric systems Jain, Anil; Nandakumar, Karthik; Ross, Arun Pattern Recognition, Vol. 38, Issue 12 https://doi.org/10.1016/j.patcog.2005.01.012	journal	December 2005

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