MLPACK: a scalable C++ machine learning library. MLPACK is a state-of-the-art, scalable, multi-platform C++ machine learning library released in late 2011 offering both a simple, consistent API accessible to novice users and high performance and flexibility to expert users by leveraging modern features of C++. MLPACK provides cutting-edge algorithms whose benchmarks exhibit far better performance than other leading machine learning libraries. MLPACK version 1.0.3, licensed under the LGPL, is available at www.mlpack.org.
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References in zbMATH (referenced in 7 articles , 1 standard article )
Showing results 1 to 7 of 7.
- Meyer, Daniel W.: Density estimation with distribution element trees (2018)
- Sanderson, Conrad; Curtin, Ryan: A user-friendly hybrid sparse matrix class in C++ (2018)
- Ryan R. Curtin, Shikhar Bhardwaj, Marcus Edel, Yannis Mentekidis: A generic and fast C++ optimization framework (2017) arXiv
- Shwartz, Ofer; Nadler, Boaz: Detecting the large entries of a sparse covariance matrix in sub-quadratic time (2016)
- Xiao, Bo; Biros, George: Parallel algorithms for nearest neighbor search problems in high dimensions (2016)
- Curtin, Ryan R.; Lee, Dongryeol; March, William B.; Ram, Parikshit: Plug-and-play dual-tree algorithm runtime analysis (2015)
- Curtin, Ryan R.; Cline, James R.; Slagle, N. P.; March, William B.; Ram, Parikshit; Mehta, Nishant A.; Gray, Alexander G.: MLPACK: a scalable C++ machine learning library (2013)