Cyanure: An Open-Source Toolbox for Empirical Risk Minimization for Python, C++, and soon more

By Julien Mairal. 2019

23 citations recorded by the source corpus.

Cyanure is an open-source C++ software package with a Python interface. The goal of Cyanure is to provide state-of-the-art solvers for learning linear models, based on stochastic variance-reduced stochastic optimization with acceleration mechanisms. Cyanure can handle a large variety of loss functions (logistic, square, squared hinge, multinomial logistic) and regularization functions (2, 1, elastic-net, fused Lasso, multi-task group Lasso). It provides a simple Python API, which is very close to that of scikit-learn, which should be extended to other languages such as R or Matlab in a near future.

Subfields: Artificial Intelligence, Computational Mechanics, Optimization & Training, Mathematical Optimization

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Citations in the corpus

Masked Siamese Networks for Label-Efficient Learning (2022, methodology): “Following (Caron et al., 2021), we use the cyanure package (Mairal, 2019) to run logistic regression on the extracted representations.”