ACL-IJCNLP 2015
TechTalks from event: ACL-IJCNLP 2015
SessionName
tutorials T1
tutorials T5
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Matrix and tensor factorization methods for natural language processingTensor 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. -
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- All Sessions
- SessionName
- tutorials T1
- tutorials T5
- tutorials T2
- tutorials T6
- tutorials T3
- tutorials T7
- tutorials T4
- tutorials T8
- session 1B Language and Vision/NLP Applications
- session 2A Machine Translation
- session 3A Language Resources
- session 4A Semantics
- session 2B Question Answering
- session 3B Sentiment Analysis: Cross-/Multi Lingual
- session 4B Sentiment Analysis
- session 1C Semantics: Embeddings
- session 2C Semantics: Distributional Approaches
- session 3C Natural Language Generation
- session 4C Summarization and Generation
- session 1D Machine Learning
- session 2D Parsing: Neural Networks
- session 3D Spoken Language Processing and Understanding
- session 4D Discourse, Coreference
- session 1E Information Extraction 1
- session 2E Information Extraction 2
- session 3E Information Extraction 3/Information Retrieval
- session 4E Language and Vision
- session 1 Machine Translation: Neural Networks
- president talk
- session 5B Machine Learning and Topic Modeling
- session 6A Discourse, Pragmatics
- session 7A Discourse, Coreference
- student research workshop
- session 5C Semantics, Linguistic and Psycholinguistic Aspects of CL
- session 6C Semantics: Semantic Parsing
- session 7C Semantics: Semantic Parsing
- session 6B Machine Learning: Embeddings
- session 7B Topic Modeling
- session 7D Lexical Semantics
- session 6D Sentiment Analysis: Learning
- session 5D Parsing, Tagging
- session 5E Information Extraction
- session 6E Grammar Induction and Annotation
- session 7E Parsing
- invited talk
- session 5A Machine Translation
- session 8B Automatic Summarization
- session 9B Word Segmentation
- session 8C Linguistic and Psycholinguistic Aspects of NLP
- session 9C Morphology, Phonology
- session 8D NLP for the Web: Social Media
- session 9D NLP for the Web: Twitter
- session 8E Text Categorization/Information Retrieval
- session 9E POS Tagging
- session 8A Machine Learning: Neural Networks
- session 9A Multilinguality
- session BP Best Paper Session