DSMML
2004
Springer
13 years 8 months ago
2004
Springer
We investigate theoretically some properties of variational Bayes approximations based on estimating the mixing coefficients of known densities. We show that, with probability 1 a...
DSMML
2004
Springer
13 years 8 months ago
2004
Springer
The arithmetic-coding-based communication system, Dasher, can be driven by a one-dimensional continuous signal. A belt-mounted breath-mouse, delivering a signal related to lung vol...
DSMML
2004
Springer
13 years 10 months ago
2004
Springer
DSMML
2004
Springer
13 years 10 months ago
2004
Springer
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 how to approximat...
DSMML
2004
Springer
13 years 10 months ago
2004
Springer
Learning curves for Gaussian process (GP) regression can be strongly affected by a mismatch between the ‘student’ model and the ‘teacher’ (true data generation process), e...
DSMML
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. Gaussian process prior systems generally consist of noisy measurements of samples of the putatively Gaussian process of interest, where the samples serve to constrain the...
DSMML
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. We present an SVM-based learning algorithm for information extraction, including experiments on the influence of different algorithm settings. Our approach needs fewer ...
DSMML
2004
Springer
13 years 10 months ago
2004
Springer
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
DSMML
2004
Springer
13 years 10 months ago
2004
Springer
Applications such as audio fingerprinting require search in high dimensions: find an item in a database that is similar to a query. An important property of this search task is t...
DSMML
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. In recent years the problem of object recognition has received considerable attention from both the machine learning and computer vision communities. The key challenge of...