LIBOL: a library for online learning algorithms. LIBOL is an open-source library for large-scale online learning, which consists of a large family of efficient and scalable state-of-the-art online learning algorithms for large-scale online classification tasks. We have offered easy-to-use command-line tools and examples for users and developers, and also have made comprehensive documents available for both beginners and advanced users. LIBOL is not only a machine learning toolbox, but also a comprehensive experimental platform for conducting online learning research.
Keywords for this software
References in zbMATH (referenced in 6 articles , 1 standard article )
Showing results 1 to 6 of 6.
- Brinkman, Daniel; Ringhofer, Christian: A kinetic games framework for insurance plans (2017)
- Liu, Chenghao; Jin, Tao; Hoi, Steven C.H.; Zhao, Peilin; Sun, Jianling: Collaborative topic regression for online recommender systems: an online and Bayesian approach (2017)
- Lu, Jing; Zhao, Peilin; Hoi, Steven C.H.: Online passive-aggressive active learning (2016)
- Huang, Shuangping; Jin, Lianwen; Xue, Kunnan; Fang, Yuan: Online primal-dual learning for a data-dependent multi-kernel combination model with multiclass visual categorization applications (2015)
- Hoi, Steven C.H.; Wang, Jialei; Zhao, Peilin: LIBOL: a library for online learning algorithms (2014)
- Zhao, Peilin; Hoi, Steven C.H.; Wang, Jialei; Li, Bin: Online transfer learning (2014)