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MCS
2000
Springer
15 years 6 months ago
Ensemble Methods in Machine Learning
Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a (weighted) vote of their predictions. The original ensembl...
Thomas G. Dietterich
147
Voted
UAI
2001
15 years 4 months ago
Markov Chain Monte Carlo using Tree-Based Priors on Model Structure
We present a general framework for defining priors on model structure and sampling from the posterior using the Metropolis-Hastings algorithm. The key ideas are that structure pri...
Nicos Angelopoulos, James Cussens
106
Voted
BMVC
2000
15 years 4 months ago
Parallel Chains, Delayed Rejection and Reversible Jump MCMC for Object Recognition
We tackle the problem of object recognition using a Bayesian approach. A marked point process [1] is used as a prior model for the (unknown number of) objects. A sample is generat...
M. Harkness, P. Green
FLAIRS
1998
15 years 4 months ago
Decision Making in Qualitative Influence Diagrams
The increasing number of knowledge-based systems that build on a Bayesian belief network or influence diagram acknowledge the usefulness of these frameworks for addressing complex...
Silja Renooij, Linda C. van der Gaag
97
Voted
WWW
2001
ACM
16 years 3 months ago
Finding authorities and hubs from link structures on the World Wide Web
Recently, there have been a number of algorithms proposed for analyzing hypertext link structure so as to determine the best "authorities" for a given topic or query. Wh...
Allan Borodin, Gareth O. Roberts, Jeffrey S. Rosen...