Error-driven learning in multilayer neural networks was revolutionized by the error backpropagation algorithm 1, or backprop for short. In backprop, gradients or ...

Human-in-the-loop machine learning takes advantage of human feedback to eliminate errors in training data and improve the accuracy of models. Machine learning models are often far from perfect. When ...

This paper provides the framework and supporting evidence for a highly efficient closed-loop paradigm that modifies a classic learning scenario using real-time brain activity in order to improve ...