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Multiple Instance Learning from Unlimited Text
Wednesday, October 28, 2015, 11:00 am-12:00 pm Calendar
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Abstract
The advent of big data provides both challenges and opportunities for processing natural language. My research focuses on scalable machine learning methods to understand the seemingly unlimited number of expressions in human language. In this talk, I will present a multiple instance learning model that learns variant expressions of the same meaning from Twitter's massive data stream. This approach is one of the first models that can jointly reason about relations between words and sentences. I will highlight its value and wide applications in natural language processing and computational social science. I will also hint at how similar models can leverage and extend large knowledge bases.
Bio
Wei Xu is a post-doctoral researcher in the Computer and Information Science Department at the University of Pennsylvania. Her research interests lie at the intersection of natural language processing, machine learning, and social media. She has received the 5-year MacCracken Fellowship and completed her PhD in 2014 from New York University. During her PhD, she visited University of Washington for two years. She is organizing the ACL Workshop on Noisy User-generated Text and serving as the publicity chair for NAACL 2016.
This talk is organized by Naomi Feldman