-
Upload Video
videos in mp4/mov/flv
close
Upload video
Note: publisher must agree to add uploaded document -
Upload Slides
slides or other attachment
close
Upload Slides
Note: publisher must agree to add uploaded document -
Feedback
help us improve
close
Feedback
Please help us improve your experience by sending us a comment, question or concern
Please help transcribe this video using our simple transcription tool. You need to be logged in to do so.
Description
Tensor and matrix factorization methods have attracted a lot of attention recently thanks to their successful applications to information extraction, knowledge base population, lexical semantics and dependency parsing. In the first part, we will first cover the basics of matrix and tensor factorization theory and optimization, and then proceed to more advanced topics involving convex surrogates and alternative losses. In the second part we will discuss recent NLP applications of these methods and show the connections with other popular methods such as transductive learning, topic models and neural networks. The aim of this tutorial is to present in detail applied factorization methods, as well as to introduce more recently proposed methods that are likely to be useful to NLP applications.