Distributed Representations of Words and Phrases and their Compositionality
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Skip-gram model is to find word representations that are useful for predicting the surrounding words in a sentence or a document
given a sequence of training words w1, w2, w3, . . . , wT , the objective of the Skip-gram model is to maximize the average log probability
Hierarchical Softmax
Negative Sampling
Noise Contrastive Estimation
differentiate data from noise by means of logistic regression
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