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Efficient Deep Learning with Decorrelated Backpropagation
This demonstrates that decorrelation provides exciting prospects for efficient deep learning at scale.
Effective Learning with Node Perturbation in Deep Neural Networks
Backpropagation (BP) is the dominant and most successful method for training parameters of deep neural network models.
Establishing phone-pair co-usage by comparing mobility patterns
In forensic investigations it is often of value to establish whether two phones were used by the same person during a given time period.
Gradient-adjusted Incremental Target Propagation Provides Effective Credit Assignment in Deep Neural Networks
Many of the recent advances in the field of artificial intelligence have been fueled by the highly successful backpropagation of error (BP) algorithm, which efficiently solves the credit assignment problem in artificial neural networks.
