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ORCIDMachine Learning, Volume 50, 2003
Volume 50, Number 1-2, January - February 2003
- Christophe Andrieu, Nando de Freitas, Arnaud Doucet
, Michael I. Jordan:
An Introduction to MCMC for Machine Learning. 5-43 - Frank Dellaert, Steven M. Seitz, Charles E. Thorpe, Sebastian Thrun:
EM, MCMC, and Chain Flipping for Structure from Motion with Unknown Correspondence. 45-71 - Ernest Fokoué, D. M. Titterington:
Mixtures of Factor Analysers. Bayesian Estimation and Inference by Stochastic Simulation. 73-94 - Nir Friedman, Daphne Koller:
Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks. 95-125 - Paolo Giudici, Robert Castelo:
Improving Markov Chain Monte Carlo Model Search for Data Mining. 127-158 - Christopher C. Holmes, Dave Denison:
Classification with Bayesian MARS. 159-173 - Kathryn B. Laskey, James W. Myers:
Population Markov Chain Monte Carlo. 175-196 - Herbert K. H. Lee:
A Noninformative Prior for Neural Networks. 197-212
Volume 50, Number 3, March 2003
- Ryszard S. Michalski, Pavel Brazdil:
Introduction. 219-222 - Ljupco Todorovski, Saso Dzeroski:
Combining Classifiers with Meta Decision Trees. 223-249 - Pavel Brazdil, Carlos Soares, Joaquim Pinto da Costa:
Ranking Learning Algorithms: Using IBL and Meta-Learning on Accuracy and Time Results. 251-277 - AnHai Doan, Pedro M. Domingos, Alon Y. Halevy:
Learning to Match the Schemas of Data Sources: A Multistrategy Approach. 279-301 - Luís Torgo, Joaquim Pinto da Costa:
Clustered Partial Linear Regression. 303-319 - Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda:
Complete Mining of Frequent Patterns from Graphs: Mining Graph Data. 321-354
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