Seminars

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Soumith Chintala (Facebook, New York) “An Overview of Deep Learning Frameworks and an Introduction to PyTorch” 12:00 pm
Soumith Chintala (Facebook, New York) “An Overview of Deep Learning Frameworks and an Introduction to PyTorch” @ Hackerman Hall B17
Sep 8 @ 12:00 pm – 1:15 pm
Absract In this talk, you will get an exposure to the various types of deep learning frameworks – declarative and imperative frameworks such as TensorFlow and PyTorch. After a broad overview of frameworks, you will[...]
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Tal Linzen (JHU) “Structure-Sensitive Dependency Learning in Recurrent Neural Networks” 12:00 pm
Tal Linzen (JHU) “Structure-Sensitive Dependency Learning in Recurrent Neural Networks” @ Hackerman Hall B17
Sep 22 @ 12:00 pm – 1:15 pm
Abstract Neural networks have recently become ubiquitous in natural language processing systems, but we typically have little understanding of specific capabilities of these networks beyond their overall accuracy in an applied task. The present work[...]
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Lambert Mathias (Amazon) “Natural Language Understanding with Heterogenous Schema” 12:00 pm
Lambert Mathias (Amazon) “Natural Language Understanding with Heterogenous Schema” @ Hackerman Hall B17
Sep 26 @ 12:00 pm – 1:15 pm
Abstract In a multi-domain conversational system, such as Alexa, a key challenge is to enable transfer of actionable information across applications. Most often these systems have evolved independently, with their own local schemas and interoperability[...]
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Satinder Singh (University of Michigan) “Deep Reinforcement Learning for Sequential Decision Making Tasks with Natural Language Interaction” 12:00 pm
Satinder Singh (University of Michigan) “Deep Reinforcement Learning for Sequential Decision Making Tasks with Natural Language Interaction” @ Hackerman Hall B17
Sep 29 @ 12:00 pm – 1:15 pm
Abstract The success of Deep Learning (DL) on visual perception has led to rapid progress on Reinforcement Learning (RL) tasks with visual inputs. More recently, Deep Learning is showing promise at certain kinds of supervised[...]
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Center for Language and Speech Processing