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NIPS
2004
13 years 11 months ago
2004
The computation and memory required for kernel machines with N training samples is at least O(N2 ). Such a complexity is significant even for moderate size problems and is prohibi...
NIPS
2004
13 years 11 months ago
2004
Survey propagation is a powerful technique from statistical physics that has been applied to solve the 3-SAT problem both in principle and in practice. We give, using only probabi...
NIPS
2004
13 years 11 months ago
2004
We propose a convex optimization based strategy to deal with uncertainty in the observations of a classification problem. We assume that instead of a sample (xi, yi) a distributio...
NIPS
2004
13 years 11 months ago
2004
We describe how we used a data set of chorale harmonisations composed by Johann Sebastian Bach to train Hidden Markov Models. Using a probabilistic framework allows us to create a...
NIPS
2004
13 years 11 months ago
2004
We present a probabilistic approach to learning a Gaussian Process classifier in the presence of unlabeled data. Our approach involves a "null category noise model" (NCN...