4 papers
Bit-wise Training of Neural Network Weights
Cristian Ivan
We introduce an algorithm where the individual bits representing the weights of a neural network are learned. This method allows training weights with integer values on arbitrary b…
Training highly effective connectivities within neural networks with randomly initialized, fixed weights
Cristian Ivan, Razvan Florian
We present some novel, straightforward methods for training the connection graph of a randomly initialized neural network without training the weights. These methods do not use hyp…
Convolutional Neural Networks on Randomized Data
Cristian Ivan
Convolutional Neural Networks (CNNs) are build specifically for computer vision tasks for which it is known that the input data is a hierarchical structure based on locally correla…
On modelling the emergence of logical thinking
Cristian Ivan, Bipin Indurkhya
Recent progress in machine learning techniques have revived interest in building artificial general intelligence using these particular tools. There has been a tremendous success i…