Machine Learning with Shallow Neural Networks



Conventional machine learning often uses optimization and gradient-descent methods for learning parameterized models. Examples of such models include linear regression, support vector machines, logistic regression, dimensionality reduction, and matrix factorization. Neural networks are also parameterized models that are learned with continuous optimization methods.


Least-squares Classification CBOW Model Gradient Descent Update Widrow-Hoff Learning Probabilistic Latent Semantic Analysis 
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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.IBM T. J. Watson Research CenterInternational Business MachinesYorktown HeightsUSA

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