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MILJS: Brand New JavaScript Libraries for Matrix Calculation and Machine Learning

Ken Miura, Tetsuaki Mano, Atsushi Kanehira, Yuichiro Tsuchiya, Tatsuya Harada
Machine Intelligence Laboratory, Department of Mechano-Informatics, The University of Tokyo
arXiv:1502.06064 [stat.ML], (21 Feb 2015)

@article{miura2015miljs,

   title={MILJS : Brand New JavaScript Libraries for Matrix Calculation and Machine Learning},

   author={Miura, Ken and Mano, Tetsuaki and Kanehira, Atsushi and Tsuchiya, Yuichiro and Harada, Tatsuya},

   year={2015},

   month={feb},

   archivePrefix={"arXiv"},

   primaryClass={stat.ML}

}

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MILJS is a collection of state-of-the-art, platform-independent, scalable, fast JavaScript libraries for matrix calculation and machine learning. Our core library offering a matrix calculation is called Sushi, which exhibits far better performance than any other leading machine learning libraries written in JavaScript. Especially, our matrix multiplication is 177 times faster than the fastest JavaScript benchmark. Based on Sushi, a machine learning library called Tempura is provided, which supports various algorithms widely used in machine learning research. We also provide Soba as a visualization library. The implementations of our libraries are clearly written, properly documented and thus can are easy to get started with, as long as there is a web browser. These libraries are available from this http URL under the MIT license.
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