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Gradient Monitored Reinforcement Learning
The proposed method which we term as Gradient Monitoring(GM), is an approach to steer the learning in the weight parameters of a neural network based on the dynamic development and feedback from the training process itself.
Learning the Non-linearity in Convolutional Neural Networks
The weights of this matrix then constitute the exponents of the corresponding components of the receptive field.
Generalized Dilation Neural Networks
One of the strengths of convolutional layers is the ability to learn features about spatial relations in the input domain using various parameterized convolutional kernels.
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