Online Co-regularized Algorithms [chapter]

Tom de Ruijter, Evgeni Tsivtsivadze, Tom Heskes
2012 Lecture Notes in Computer Science  
We propose an online co-regularized learning algorithm for classification and regression tasks. We demonstrate that by sequentially co-regularizing prediction functions on unlabeled data points, our algorithm provides improved performance in comparison to supervised methods on several UCI benchmarks and a real world natural language processing dataset. The presented algorithm is particularly applicable to learning tasks where large amounts of (unlabeled) data are available for training. We also
more » ... provide an easy to set-up and use Python implementation of our algorithm 3 .
doi:10.1007/978-3-642-33492-4_16 fatcat:flirzx2pejfpdgd65pcs5bsqme