Seminars

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Lea Frermann (University of Melbourne) “Learning Representations of Long Narratives for Summarization and Inference” 12:00 pm
Lea Frermann (University of Melbourne) “Learning Representations of Long Narratives for Summarization and Inference” @ Hackerman Hall B17
Apr 1 @ 12:00 pm – 1:15 pm
Abstract Humans have an impressive ability to understand long and complex narratives, and to utilize common sense knowledge to quickly comprehend novel situations. NLP systems tend to scale poorly to long texts, and to rely[...]
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Heng Ji (RPI) Universal Information Extraction 12:00 pm
Heng Ji (RPI) Universal Information Extraction @ Hackerman Hall B17
Apr 5 @ 12:00 pm – 1:15 pm
Abstract The big data boom in recent years covers a wide spectrum of heterogeneous data types, from text to image, video, speech, and multimedia. Most of the valuable information in such “big data” is encoded[...]
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Nazli Goharian (Georgetown University)”Social Media and Mental Health” 12:00 pm
Nazli Goharian (Georgetown University)”Social Media and Mental Health” @ Hackerman Hall B17
Apr 8 @ 12:00 pm – 1:15 pm
Abstract With the ever-increasing usage of social media for either explicitly seeking help or simply sharing thoughts and feelings, we, in the computational disciplines, have the opportunity to utilize such data for building datasets, models,[...]
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David Snyder 12:00 pm
David Snyder @ Hackerman Hall B17
Apr 15 @ 12:00 pm – 1:15 pm
 
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DeLiang Wang (Ohio State University) “Towards Solving the Cocktail Party Problem” 12:00 pm
DeLiang Wang (Ohio State University) “Towards Solving the Cocktail Party Problem” @ Hackerman Hall B17
Apr 26 @ 12:00 pm – 1:15 pm
Abstract The cocktail party problem, or speech separation, has evaded a solution for decades in speech and audio processing. I have been advocating a new formulation of this old challenge that estimates an ideal time-frequency[...]
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Le Song (Georgia Institute of Technology) “Can Graph Neural Networks Help Logic Inference?” 12:00 pm
Le Song (Georgia Institute of Technology) “Can Graph Neural Networks Help Logic Inference?” @ Hackerman Hall B17
Apr 29 @ 12:00 pm – 1:15 pm
Abstract Combining perceptual learning and logic inference/symbolic reasoning has been a long standing goal of AI. Graph neural networks are powerful representation learning tools for graph data, including but not limited to social networks, molecular[...]
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Center for Language and Speech Processing