Large-scale multiclass transduction
Thomas Gaertner, quoc le, Simon Burton, Alex Smola and S V N Vishwanathan
In: NIPS 2005, December 2005, Vancouver.
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 performed sufficiently fast. This holds, for instance,
for certain graph and string kernels. Transduction is achieved by varia-
tional inference over the unlabeled data subject to a balancing constraint.