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NIPS
2004
15 years 2 months ago
2004
The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit. In this paper we show (1) how to appro...
98
Voted
NIPS
2004
15 years 2 months ago
2004
Go is an ancient oriental game whose complexity has defeated attempts to automate it. We suggest using probability in a Bayesian sense to model the uncertainty arising from the va...
109
Voted
NIPS
2004
15 years 2 months ago
2004
We propose the hierarchical Dirichlet process (HDP), a nonparametric Bayesian model for clustering problems involving multiple groups of data. Each group of data is modeled with a...
80
Voted
NIPS
2004
15 years 2 months ago
2004
We propose a family of kernels based on the Binet-Cauchy theorem and its extension to Fredholm operators. This includes as special cases all currently known kernels derived from t...
NIPS
2004
15 years 2 months ago
2004
Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...