An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
We use the concept of conditional mutual information (MI) to approach problems involving the selection of variables in the area of medical diagnosis. Computing MI requires estimate...
I propose a uniform approach to the elimination of redundancy in CCG lexicons, where grammars incorporate inheritance hierarchies of lexical types, defined over a simple, feature-...
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
ct We describe work on the visualization of bibliographic data and, to aid in this task, the application of numerical techniques for multidimensional scaling. Many areas of scienti...