I’ll be talking about some recent work in classifier design.
The title of my talk will be “Using Competition to Design a Modified Bayes Classifier”.
A modified naive Bayes classifier represents the joint statistics of small subsets of variables while treating the subsets as statistically independent. This talk introduces an automatic training method that decomposes the variables into such subsets. The training method generates a large set of candidate subsets and trains “sub-classifiers” over each subset. An empirically-based competition selects a combination of these sub-classifiers to form the overall classifier. Using this method, I have constructed object detectors for human faces and telephones.