Combining machine learning models is a means of improving overall accuracy.Various algorithms have been proposed to create aggregate models from other models, and two popular examp...
We consider PAC-learning where the distribution is known to the student. The problem addressed here is characterizing when learnability with respect to distribution D1 implies lea...
- The rapid growth in the amount of molecular genetic data being collected will, in many cases, require the development of new analytic methods for the analysis of that data. In th...
Robust reasoning requires learning from problem solving episodes. Past experience must be compiled to provide adaptation to new contingencies and intelligent modification of solut...
This paper addresses the issue of reducing the storage requirements on Instance-Based Learning algorithms. Algorithms proposed by other researches use heuristics to prune instance...