This volume, written by leading researchers, presents methods of
combining neural nets to improve their performance. The techniques
include ensemble-based approaches, where a variety of methods are
used to create a set of different nets trained on the same task,
and modular approaches, where a task is decomposed into simpler
problems. The techniques are also accompanied by an evaluation of
their relative effectiveness and their application to a variety of
problems.
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