'Missing variables' presentation slideshows

Missing variable problems

Missing variable problems. In many vision problems, if some variables were known the maximum likelihood inference problem would be easy fitting; if we knew which line each token came from, it would be easy to determine line parameters

445 views • 34 slides

Combining Information from Related Regressions

Combining Information from Related Regressions. F. Dominici, G. Parmigiani, K. H. Reckhow and R. L. Wolpert, JABES 1997. Duke University Machine Learning Group Presented by Kai Ni Apr. 27, 2007. Outline. Introduction Model Results Conclusion. Motivation. The general problem

268 views • 16 slides

Quine-McCluskey Minimization Algorithm

337 views • 12 slides