Convolution kernels, constructed by convolution of sub-kernels defined on sub-structures of composite objects, are widely used in classification, where one important issue is to ch...
The meta-learner MLR (Multi-response Linear Regression) has been proposed as a trainable combiner for fusing heterogeneous baselevel classifiers. Although it has interesting prope...
We study local interchangeability of values in constraint networks based on a new approach where a single value in the domain of a variable can be treated as a combination of &quo...
We address the following sensor selection problem. We assume that a dynamic system possesses a certain property, call it Property D, when a set G of sensors is used. There is a cos...
Abstract. One of the most appealing features of constraint programming is its rich constraint language for expressing combinatorial optimization problems. This paper demonstrates t...