Unified integration of explicit knowledge and learning by example in recurrent networks
Paolo Frasconi, Marco Gori, Marco Maggini, G. Soda · IEEE Transactions on Knowledge and Data Engineering · 1995
Proposes a novel unified approach for integrating explicit knowledge and learning by example in recurrent networks. The explicit knowledge is represented by automaton rules, which are directly injected into the connections of a network. This can be accomplished by using a technique based on linear programming, instead of learning from random initial weights. Learning is conceived as a refinement process and is mainly responsible for uncertain information management. We present preliminary results for problems of automatic speech recognition.>