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Vowpal Wabbit

swMATH ID: 28398
Software Authors: Langford, L. Li, A. Strehl
Description: The Vowpal Wabbit (VW) project is a fast out-of-core learning system sponsored by Microsoft Research and (previously) Yahoo! Research. Support is available through the mailing list. There are two ways to have a fast learning algorithm: (a) start with a slow algorithm and speed it up, or (b) build an intrinsically fast learning algorithm. This project is about approach (b), and it’s reached a state where it may be useful to others as a platform for research and experimentation. There are several optimization algorithms available with the baseline being sparse gradient descent (GD) on a loss function (several are available), The code should be easily usable. Its only external dependence is on the boost library, which is often installed by default.
Homepage: https://github.com/VowpalWabbit/vowpal_wabbit/wiki
Related Software: GitHub; UCI-ml; R; HOGWILD; PyTorch; TensorFlow; Spark; MASS (R); LBFGS-B; NVBLAS; Scikit; Armadillo; SHOGUN; L-BFGS-B; Matlab; Optim; Autograd; Numba; Adam; SciPy
Referenced in: 9 Publications

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