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We describe an algorithm called Divide and Conquer Neural Networks (DCN), which creates a feedforward neural network architecture during training, based upon the training examples. The first cell introduced on any layer is trained on all examples.
In this paper two algorithms for the construction of feedforward neural network architectures are discussed. Their close relation with a special class of ...
DIVIDE AND CONQUER ALGORITHMS FOR CONSTRUCTING. NEURAL NETWORKS ARCHITECTURES. K. KOUTROUMBAS A. POULIAKIS and N. KALOUPTSIDIS. Abstract| In this paper two ...
Nov 8, 2016 · This principle creates a powerful inductive bias that we leverage with neural architectures that are defined recursively and dynamically, by ...
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This principle creates a powerful inductive bias that we leverage with neural architectures that are defined recursively and dynamically, by learning two scale-.
Abstract: An efficient method of constructing mapping neural networks based on the divide-and-conquer principle is presented. The network thus constructed ...
In this section we present our basic model architecture with its core Split and Merge blocks, and then describe how to build the global dynamic programming ...
We describe an algorithm called Divide and Conquer Neural Networks (DCN), which creates a feedforward neural network architecture during training, based upon ...
A divide-and-conquer algorithm is used to distribute the input data of the complex problem to a divided radial basis function neural network (Div-RBFNN).
May 17, 2017 · This work considers the learning of algorithmic tasks by mere observation of input- output pairs. Rather than studying this as a black-box ...