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In machine learning, backpropagation is a gradient estimation method commonly used for training a neural network to compute its parameter updates. It is an efficient application of the chain rule to neural networks.
A Hopfield network (or associative memory) is a form of recurrent neural network, or a spin glass system, that can serve as a content-addressable memory.The Hopfield network, named for John Hopfield, consists of a single layer of neurons, where each neuron is connected to every other neuron except itself.
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Seppo Ilmari Linnainmaa (born 28 September 1945) is a Finnish mathematician and computer scientist known for creating the modern version of backpropagation. Biography [ edit ]
Backpropagation through time (BPTT) is a gradient-based technique for training certain types of recurrent neural networks, such as Elman networks. The algorithm was independently derived by numerous researchers.
Among the fast food giants, McDonald's is making a splash with its new value platform starting on Jan. 7, its first national value offering since 2018.Bernstein analyst Danilo Gargiulo called it a ...
Paul John Werbos (born September 4, 1947) is an American social scientist and machine learning pioneer. He is best known for his 1974 dissertation, which first described the process of training artificial neural networks through backpropagation of errors. [1]
The electric vehicle market could get a huge influx of cheaper cars — but not fresh from the factory. In its latest EV intelligence report, consumer research firm J.D. Power projects that a ...