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Attention (machine learning) - Wikipedia
Attention is a machine learning method that determines the relative importance of each component in a sequence relative to the other components in that sequence. In natural language processing, importance is represented by "soft" weights assigned to each word in a sentence. More generally, … 展开
Academic reviews of the history of the attention mechanism are provided in Niu et al. and Soydaner.
Predecessors
Selective attention in … 展开Many variants of attention implement soft weights, such as
• fast weight programmers, or fast weight controllers (1992). A "slow" neural network outputs the "fast" weights of another neural network through outer products. The slow network learns … 展开• Dan Jurafsky and James H. Martin (2022) Speech and Language Processing (3rd ed. draft, January 2022), ch. 10.4 Attention and ch. 9.7 Self-Attention Networks: Transformers
• Alex Graves (4 May 2020), Attention and Memory in Deep Learning (video … 展开The attention network was designed to identify high correlations patterns amongst words in a given sentence, assuming that it has learned word correlation patterns from the training data. This correlation is captured as neuronal weights learned during training with 展开
Tasks dealing with language can be cast as a problem of translating general sequences, called seq2seq. One way to build such a machine in 2014 is to graft an attention unit to the recurrent Encoder-Decoder (diagram below). With the advent of Transformers in 2017, … 展开
CC-BY-SA 许可证中的维基百科文本 Machine learning - Wikipedia
Transformer (deep learning architecture) - Wikipedia
网页A transformer is a deep learning architecture developed by researchers at Google and based on the multi-head attention mechanism, proposed in a 2017 paper "Attention Is All You Need". [1] Text is converted to …
What Is Attention? - MachineLearningMastery.com
Attention Models Definition - DeepAI
网页Attention models have emerged as a powerful technique in deep learning, particularly in the fields of natural language processing (NLP) and computer vision. They are designed to enhance the performance of neural …
Attention in Psychology, Neuroscience, and Machine …
网页2020年4月15日 · Attention mechanisms in machine learning allow a single trained artificial neural network to perform well on multiple tasks or tasks with inputs of variable length, size, or structure.
Attention in Psychology, Neuroscience, and Machine Learning
Attention - AI Wiki - Artificial Intelligence, Machine Learning Wiki ...
Attention — The Science of Machine Learning & AI
网页Attention. Attention mechanisms let a Machine Learning model relate tokens, such as words, to each other regardless of their distance between one another in a group, such as a document or group of documents. …
Interactive guide to Attention Mechanism by Kemal …
网页2021年5月15日 · The attention mechanism is one of the most important inventions in Machine Learning, at this moment (2021) it’s used to achieve impressive results in almost every field of ML, and today I want to explain …