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Xu Tan, Yi Ren, Di He, Tao Qin, Zhou Zhao, and Tie-Yan Liu. 2019 · 1902
Earlier work this paper cites.
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Raphael Tang, Yao Lu, Linqing Liu, Lili Mou, Olga Vechtomova, and Jimmy Lin. 2019 · 1903
Earlier work this paper cites.
An empirical comparison of voting classification algorithms: Bagging, boosting, and variants
Eric Bauer and Ron Kohavi. 1999 · 1999
Earlier work this paper cites.
Popular ensemble methods: An empirical study
David Opitz and Richard Maclin. 1999 · 1999
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
Analysis of representations for domain adaptation
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Earlier work this paper cites.
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Earlier work this paper cites.
Introduction to information retrieval , volume 39
Hinrich Schütze, Christopher D Manning, and Prabhakar Raghavan. 2008 · 2008
Earlier work this paper cites.
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Earlier work this paper cites.
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Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. 2011 · 2011
Earlier work this paper cites.
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