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Turing machine and decision tree have developed independently for a longtime. With the recent development of differentiable models, there is anintersection between them. Neural turing machine(NTM) opens door for the memorynetwork. It use differentiable attention mechanism to read/write externalmemory bank. Differentiable forest brings differentiable properties toclassical decision tree. In this short note, we show the deep connectionbetween these two models. That is: differentiable forest is a special case ofNTM. Differentiable forest is actually decision tree based neural turingmachine. Based on this deep connection, we propose a response augmenteddifferential forest (RaDF). The controller of RaDF is differentiable forest,the external memory of RaDF are response vectors which would be read/write byleaf nodes.

A short note on the decision tree based neural turing machine