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Invited Talk
Emily Denton
Author Information
Emily Denton (New York University)
Emily Denton is a Research Scientist at Google where they examine the societal impacts of AI technology. Their recent research centers on critically examining the norms, values, and work practices that structure the development and use of machine learning datasets. Prior to joining Google, Emily received their PhD in machine learning from the Courant Institute of Mathematical Sciences at New York University, where they focused on unsupervised learning and generative modeling of images and video.
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2021 : Case Study »
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2021 : Whose ground truth? Challenging the mythical objective, neutral standpoint »
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2021 Tutorial: Beyond Fairness in Machine Learning »
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2017 Workshop: Learning Disentangled Features: from Perception to Control »
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2017 Poster: Unsupervised Learning of Disentangled Representations from Video »
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2017 Spotlight: Unsupervised Learning of Disentangled Representations from Video »
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2016 : Discussion panel »
Ian Goodfellow · Soumith Chintala · Arthur Gretton · Sebastian Nowozin · Aaron Courville · Yann LeCun · Emily Denton -
2015 Poster: Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks »
Emily Denton · Soumith Chintala · arthur szlam · Rob Fergus -
2014 Poster: Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation »
Emily Denton · Wojciech Zaremba · Joan Bruna · Yann LeCun · Rob Fergus