Many real processes are composed of a n-fold repetition of some simpler process. If the whole process can be modelled with a neural network, we present a method to derive a model ...
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
Propositional STRIPS planning problems can be viewed as finite state automata (FSAs) represented in a factored form. Automaton minimization is a well-known technique for reducing ...
There are many applications in which it is desirable to order rather than classify instances. Here we consider the problem of learning how to order, given feedback in the form of ...
William W. Cohen, Robert E. Schapire, Yoram Singer
We address the problem of automatically acquiring case frame patterns (selectional patterns) from large corpus data. In particular, we l)ropose a method of learning dependencies b...