Jason D. Lee
About
Jason D. Lee has authored 61 papers that have received a total of 2.2k indexed citations.
This includes 40 papers in Artificial Intelligence, 13 papers in Computer Vision and Pattern Recognition and 13 papers in Computational Mechanics. The topics of these papers are Stochastic Gradient Optimization Techniques (22 papers), Sparse and Compressive Sensing Techniques (13 papers) and Statistical Methods and Inference (12 papers). Jason D. Lee is often cited by papers focused on Stochastic Gradient Optimization Techniques (22 papers), Sparse and Compressive Sensing Techniques (13 papers) and Statistical Methods and Inference (12 papers) and collaborates with scholars based in United States, China and Israel. Jason D. Lee's co-authors include Yuekai Sun, Jonathan Taylor, Michael I. Jordan, Sham M. Kakade and Nathan Srebro and has published in prestigious journals such as Journal of the American Statistical Association, IEEE Transactions on Information Theory and The Annals of Statistics
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