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Machine perception is a key step toward artificial intelligence in domains such as self-driving cars, industrial automation, and robotics. Much progress has been made in the past decade, driven by…
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Jan Ernst Date
11/30/2018
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In this talk, I will discuss my group's recent work on state-of-the-art natural language generation (NLG) and dialogue models that are multimodal, personality-based, and knowledge-rich. First,…
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Mohit Bansal Date
11/19/2018
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Given the dramatic successes in machine learning and reinforcement
learning over the past half decade, there has been a surge of interest in
applying these techniques to continuous control problems…
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Benjamin Recht Date
11/14/2018
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The retail industry is the midst of rapid change due to intensifying competition from fragmented and non-traditional sources, expansion of assortment breadth and product availability, and more…
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Graham Poliner Date
10/31/2018
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Traditional sensor data can be augmented with new data sources such as roadmaps and geographical information system (GIS) Lidar/video to offer emerging unmanned aircraft systems (UAS) and urban air…
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Ella Atkins Date
11/07/2018
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A lot of the recent progress on many AI tasks enabled in part by the availability of large quantities of labeled data. Yet, humans are able to learn concepts from as little as a handful of examples.…
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Hugo Larochelle Date
10/15/2018
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Deep learning has enabled rapid progress in diverse problems in vision, speech, healthcare, and beyond. This progress has been driven by breakthroughs in algorithms that can harness massive datasets…
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Gregory Diamos biography
Greg Diamos leads computer systems research at Baidu’s Silicon Valley AI Lab (SVAIL), where he helped develop the Deep Speech and Deep Voice systems. Date
10/03/2018
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Automated decision-making tools are currently used in high stakes scenarios. From natural language processing tools used to automatically determine one’s suitability for a job, to health…
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Timnit Gebru biography
Timnit Gebru just finished her postdoc at Microsoft Research, New York City in the FATE (Fairness Transparency Accountability and Ethics in AI) group, where she studied algorithmic bias and the ethical implications underlying any data mining project. Date
09/05/2018
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Deep learning has improved performance on many natural language processing (NLP) tasks individually. However, general NLP models cannot emerge within a paradigm that focuses on the particularities of…
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Bryan McCann biography
Bryan McCann is a Senior Research Scientist at Salesforce. He focuses on transfer learning and multitask learning for natural language processing. Most recently, Bryan proposed the Natural Language Decathlon (decaNLP) and a Multitask Question Answering Network to tackle all ten tasks in decaNLP. Before decaNLP, he showed that the intermediate representations, or context vectors (CoVe), of machine translation systems carry information that aids learning in question answering and text classification systems. Prior to working at Salesforce, Bryan studied at Stanford University, where he completed a B.S and M.S in Computer Science as well as a B.A in Philosophy. Date
08/28/2018
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In this talk, we will cover general info about Samsung Research America and more specifically the research and projects happening within the Artificial Intelligence team including personal…
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Anna Almejo, Mason Bretan Date
04/17/2018
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