The dropout learning algorithm - Baldi, Pierre; Sadowski, Peter (Artificial intelligence, 2014)
Keywords: Applied sciences; Approximation; Artificial intelligence; Backpropagation; Computer science; control theory; systems; Connectionism. Neural networks; Detection, estimation, filtering, equalization, prediction; Dropouts; Ensemble; Exact sciences and technology; Functions (mathematics); Geometric mean; Information, signal and communications theory; Learning and adaptive systems; Logistics; Machine learning; Mathematical analysis; Networks; Neural networks; Regularization; Signal and communications theory; Signal, noise; Sparse representations; Stochastic gradient descent; Stochastic neurons; Stochasticity; Telecommunications and information theory; Training; Variance minimization; Backpropagation; Neural networks; Geometric mean; Variance minimization; Machine learning; Ensemble; Sparse representations; Stochastic gradient descent; Regularization; Stochastic neurons; Ergodic theory; On line; Self consistency; Dynamic properties; Modeling; Adaptive method; Varying speed; Variance; Gradient descent; Backpropagation algorithm; Sparse representation; Transfer function; Learning algorithm; Logistic function; Static properties; Minimization; Neural network; Independent variable; Linearity; Artificial intelligence; Logistics; sparse representations; backpropagation; neural networks; regularization; variance minimization; stochastic neurons; ensemble; machine learning; stochastic gradient descent; geometric mean