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Online Co-regularized Algorithms
[chapter]
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
doi:10.1007/978-3-642-33492-4_16
fatcat:flirzx2pejfpdgd65pcs5bsqme