Jiaming Song
Stanford University
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Publication
Featured researches published by Jiaming Song.
Ai Magazine | 2018
Hongyu Ren; Russell Stewart; Jiaming Song; Volodymyr Kuleshov
In many applications of machine learning, labeled data is scarce and obtaining additional labels is expensive. We introduce a new approach to supervising learning algorithms without labels by enforcing a small number of domain-specific constraints over the algorithms’ outputs. The constraints can be provided explicitly based on prior knowledge — e.g. we may require that objects detected in videos satisfy the laws of physics — or implicitly extracted from data using a novel framework inspired by adversarial training. We demonstrate the effectiveness of constraint-based learning on a variety of tasks — including tracking, object detection, and human pose estimation — and we find that algorithms supervised with constraints achieve high accuracies with only a small amount of labels, or with no labels at all in some cases.
neural information processing systems | 2017
Yunzhu Li; Jiaming Song
international conference on machine learning | 2017
Shengjia Zhao; Jiaming Song
arXiv: Learning | 2017
Shengjia Zhao; Jiaming Song
neural information processing systems | 2017
Jiaming Song; Shengjia Zhao
arXiv: Learning | 2017
Shengjia Zhao; Jiaming Song
neural information processing systems | 2017
Yunzhu Li; Jiaming Song
neural information processing systems | 2018
Jiaming Song; Hongyu Ren; Dorsa Sadigh
uncertainty in artificial intelligence | 2018
Shengjia Zhao; Jiaming Song
neural information processing systems | 2018
Shengjia Zhao; Hongyu Ren; Arianna Yuan; Jiaming Song; Noah D. Goodman