Hidden layer

A layer in a neural network between the input layer (the features) and the output layer (the prediction). Each hidden layer consists of one or more neurons. A deep neural network contains more than one hidden layer.¹

Footnotes

developers.google.com/machine-learning/glossary#hidden-layer

역전파 이 글을 인용: “During the backward pass (backpropagation), the system reduces loss by adjusting the weights of all the neurons…”
Wide model 이 글을 인용: “We refer to it as "wide" since such a model is a special type of neural network with a large number of inputs t…”
Embedding layer 이 글을 인용: “A special hidden layer that trains on a high-dimensional categorical feature to gradually learn a lower dimensi…”
순환 신경망 이 글을 인용: “Specifically, hidden layers from the previous run provide part of the input to the same hidden layer in the nex…”
Connectionist approaches to language “A class of Recurrent neural network with feedback connections is subject to the following principle: The networ…”
Web Neural Network API “The Web Neural Network API defines a web-friendly hardware-agnostic abstraction layer that makes use of Machine…”
Evolving artificial neural networks “There has been a great interest in combining learning and evolution with artificial neural networks (ANNs) in r…”
Deep Residual Learning for Image Recognition “We explicitly reformulate the layers as learning residual functions with reference to the layer inputs, instead…”
Dense layer 이 글을 인용: “A hidden layer in which each neuron is connected to every neuron in the subsequent hidden layer.”
Nested Learning: The Illusion of Deep Learning Architectures “Over the last decades, developing more powerful neural architectures and simultaneously designing optimization …”
Sparse features “If the one-hot encoding is big, you might put an embedding layer on top of the one-hot encoding for greater eff…”
The bitter lesson “Modern deep-learning neural networks use only the notions of convolution and certain kinds of invariances, and …”
Vanishing gradient problem 이 글을 인용: “The tendency for the gradients of early hidden layers of some DNNs to become surprisingly flat (low).”
합성곱 신경망 “A neural network in which at least one layer is a convolutional layer.”
A simple way to prevent neural networks from overfitting “The key idea is to randomly drop units (along with their connections) from the neural network during training.”
Large Language Model Hacking: Quantifying the Hidden Risks of Using LLMs for Text Annotation “However, LLM outputs vary significantly depending on the implementation choices made by researchers (e.g., mode…”
모델 (기계학습) “A set of hidden layers, each containing one or more neurons.”
Memory Layers at Scale “On downstream tasks, language models augmented with our improved memory layer outperform dense models with more…”