The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Currently in document retrieval there are many algorithms each with different strengths and weakness. There is some difficulty, however, in evaluating the impact of the test quer...
It has been observed that there are a variety of situations in which the most popular hybrid simulation methods can fail to properly detect the occurrence of discrete events. In th...
We describe three applications in computational learning theory of techniques and ideas recently introduced in the study of parameterized computational complexity. (1) Using param...
Rodney G. Downey, Patricia A. Evans, Michael R. Fe...
We present a theory for constructing linear subspace approximations to face-recognition algorithms and empirically demonstrate that a surprisingly diverse set of face-recognition a...