Add to ORKGIn a multi-layered neural network, anyone of the hidden layers can be viewed as computing a distributed representation of the input. Several "encoder " experiments have shown that when the representation space is small it can be fully used. But computing with such a representation requires completely dependable nodes. In the case where the hidden nodes are noisy and unreliable, we find that error correcting schemes emerge simply by using noisy units during training; random errors in-jected during backpropagation result in spreading representations apart. Average and minimum distances increase with misfire probability, as predicted by coding-theoretic considerations. Furthennore, the effect of this noise is to protect the machine a...
It has been an open question in deep learning if fault-tolerant computation is possible: can arbitra...
The problem of neural network association is to retrieve a previously memorized pattern from its noi...
Neural networks capable of encoding sets of patterns are analysed. Solutions are found by theoretica...
[[abstract]]The fault tolerance of the multi-layer perceptron is strongly related to its redundant h...
In [2, 3, 4] error correcting codes are used to encode the output of feed-forward neural nets. We st...
In error-driven distributed feedforward networks, new information typically interferes, sometimes se...
Though deep learning has been applied successfully in many scenarios, malicious inputs with human-im...
Wide attention was recently given to the problem of fault-tolerance in neural networks; while most a...
Though deep learning has been applied successfully in many scenarios, malicious inputs with human-im...
International audienceFor many types of integrated circuits, accepting larger failure rates in compu...
International audienceFor many types of integrated circuits, accepting larger failure rates in compu...
International audienceFor many types of integrated circuits, accepting larger failure rates in compu...
International audienceFor many types of integrated circuits, accepting larger failure rates in compu...
In artificial neural networks, learning from data is a computationally demanding task in which a lar...
In error-driven distributed feedforward networks, new information typi-cally interferes, sometimes s...
It has been an open question in deep learning if fault-tolerant computation is possible: can arbitra...
The problem of neural network association is to retrieve a previously memorized pattern from its noi...
Neural networks capable of encoding sets of patterns are analysed. Solutions are found by theoretica...
[[abstract]]The fault tolerance of the multi-layer perceptron is strongly related to its redundant h...
In [2, 3, 4] error correcting codes are used to encode the output of feed-forward neural nets. We st...
In error-driven distributed feedforward networks, new information typically interferes, sometimes se...
Though deep learning has been applied successfully in many scenarios, malicious inputs with human-im...
Wide attention was recently given to the problem of fault-tolerance in neural networks; while most a...
Though deep learning has been applied successfully in many scenarios, malicious inputs with human-im...
International audienceFor many types of integrated circuits, accepting larger failure rates in compu...
International audienceFor many types of integrated circuits, accepting larger failure rates in compu...
International audienceFor many types of integrated circuits, accepting larger failure rates in compu...
International audienceFor many types of integrated circuits, accepting larger failure rates in compu...
In artificial neural networks, learning from data is a computationally demanding task in which a lar...
In error-driven distributed feedforward networks, new information typi-cally interferes, sometimes s...
It has been an open question in deep learning if fault-tolerant computation is possible: can arbitra...
The problem of neural network association is to retrieve a previously memorized pattern from its noi...
Neural networks capable of encoding sets of patterns are analysed. Solutions are found by theoretica...