nips nips2005 nips2005-105 nips2005-105-reference knowledge-graph by maker-knowledge-mining
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Author: Thomas Gärtner, Quoc V. Le, Simon Burton, Alex J. Smola, Vishy Vishwanathan
Abstract: We present a method for performing transductive inference on very large datasets. Our algorithm is based on multiclass Gaussian processes and is effective whenever the multiplication of the kernel matrix or its inverse with a vector can be computed sufficiently fast. This holds, for instance, for certain graph and string kernels. Transduction is achieved by variational inference over the unlabeled data subject to a balancing constraint. 1
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