Multi-Task Feature Selection on Multiple Networks via Maximum Flows

Sugiyama, M.; Azencott, C.-A.; Grimm, D.; Kawahara, Y.; Borgwardt, K. M.

doi:10.1137/1.9781611973440.23

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Multi-Task Feature Selection on Multiple Networks via Maximum Flows

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Azencott, C.-A.
Research Group Machine Learning and Computational Biology, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Grimm, D.
Dept. Empirical Inference, Max Planck Institute for Intelligent System, Max Planck Society;

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Borgwardt, K. M.
Research Group Machine Learning and Computational Biology, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Sugiyama, M., Azencott, C.-A., Grimm, D., Kawahara, Y., & Borgwardt, K. M. (2014). Multi-Task Feature Selection on Multiple Networks via Maximum Flows. In M. Zaki (Ed.), Proceedings of the 2014 SIAM International Conference on Data Mining (pp. 199-207). Society for Industrial and Applied Mathematics (SIAM). doi:10.1137/1.9781611973440.23.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0025-BC05-1

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