Online Matrix Factorization for Space Embedding Multilabel Annotation [chapter]

Sebastian Otálora-Montenegro, Santiago A. Pérez-Rubiano, Fabio A. González
2013 Lecture Notes in Computer Science  
The paper presents an online matrix factorization algorithm for multilabel learning. This method addresses the multi-label annotation problem finding a joint embedding that represents both instances and labels in a common latent space. An important characteristic of the novel method is its scalability, which is a consequence of its formulation as an online learning algorithm. The method was systematically evaluated in different standard datasets and compared against state-of-the-art space
more » ... ing multi-label learning algorithms showing competitive results.
doi:10.1007/978-3-642-41822-8_43 fatcat:mfeovm7pnneetmmit5hj2rxlkq