Neural Information Processing Systems / Neural Networks / Deep Convolutional Neural Networks / Multilayer Neural Networks / MIT Press / Acoustic Modeling Using Deep Belief Networks / / /
Facility
Applied Physics Stanford University / /
IndustryTerm
deep linear networks / dot products / layer network / energy function / shallow network / even accounting / much deeper networks / deep learning systems / analytical solutions / shallow networks / deep networks / natural language processing / linear network / nonlinear networks / deep linear network / deep non-linear networks / deeper networks / time-dependent solutions / explicit solution / deep network / linear networks / nonlinear network / error solutions / layer linear network / learning algorithms / /
Organization
Cognitive Science Society / MIT / Stanford University / Association for Computational Linguistics Conference / Department of Psychology Surya Ganguli / Department of Electrical Engineering James L. McClelland / /
Person
Andrew M. Saxe / James L. McClelland / Large-Scale Kernel Machines / /
Position
General / /
ProvinceOrState
California / /
PublishedMedium
Machine Learning / Journal of Machine Learning Research / /
Dynamics of learning in deep linear neural networks Andrew M. Saxe ([removed]) Department of Electrical Engineering James L. McClelland ([removed])