Multiple instance (MI) learning is a recent learning paradigm that is more flexible than standard supervised learning algorithms in the handling of label ambiguity. It has been u...
Abstract—In the analysis of spatially-referenced timedependent
data, gaining an understanding of the spatiotemporal
distributions and relationships among the attributes
in the...
In the field of pattern recognition, multiple classifier systems based on the combination of outputs of a set of different classifiers have been proposed as a method for the devel...
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
We present a new rigging and skinning method which uses a database of partial rigs extracted from a set of source characters. Given a target mesh and a set of joint locations, our...