An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression
Kwangmoo Koh and Seung-Jean Kim and Stephen Boyd

An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression.pdf 910.98kB
Type: Paper
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@article{8:54,author={Kwangmoo Koh and Seung-Jean Kim and Stephen Boyd}, Title={An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression},journal={Journal of Machine Learning Research},volume={8}, url={http://www.jmlr.org/papers/volume8/koh07a/koh07a.pdf}}
Citation:
Koh, K., Kim, S., & Boyd, S.. (2014). An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression [Data set]. Academic Torrents. https://academictorrents.com/details/2deb1384378d8b6b777db438b4f57ff7866274a5

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