Deep Learning the Precise Meaning of Language
Human languages begin by encoding a lot of meaning in words but, above that level, they use the structure of sentences to convey complex information. In this talk I will look at how we can better understand the meaning of words, how we can use Tree-structured Recursive Neural Networks to more accurately parse and understand the meanings and sentiment of sentences, and how these techniques can be used for more nuanced translation between languages.
Christopher Manning is a professor of computer science and linguistics at Stanford University. He works on software that can intelligently process, understand, and generate human language material. He is a leader in applying Deep Learning to Natural Language Processing, including exploring Tree Recursive Neural Networks, sentiment analysis, neural network dependency parsing, the GloVe model of word vectors, neural machine translation, and deep language understanding. Manning is an ACM Fellow, a AAAI Fellow, and an ACL Fellow, and has coauthored leading textbooks on statistical natural language processing and information retrieval. He is a member of the Stanford NLP group (@stanfordnlp).