Carat: collaborative energy diagnosis for mobile devices

Untitled work

(2010) · Cited by 4,411

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Murthy, S. K. (1998) · Data Mining and Knowledge Discovery · doi:10.1023/a:1009744630224 · Cited by 1,085

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Chen, M. Y., Kıcıman, E., Fratkin, E., Fox, A., & Brewer, E. (2003) · International Conference on Dependable Systems & Networks/Proceedings · doi:10.1109/dsn.2002.1029005 · Cited by 846

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Vigilante

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