Julian Katz-Samuels

I am a PhD candidate in the Electrical Engineering and Computer Science Department at the University of Michigan. My advisor is Prof. Clayton Scott. My research focuses on pure exploration multi-armed bandits, recommender systems, and nonparametric estimation. I am also interested in applications of machine learning that promote the social good. As a Data Science for Social Good fellow at the University of Chicago in 2015, I helped develop the Legislative Influence Detector. I completed my undergraduate studies at the University of Chicago, where I double-majored in mathematics and philosophy.

 

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Publications

 

  • Dejiao Zhang, Julian Katz-Samuels, Mario A.T. Figueiredo, and Laura Balzano, "Simultaneous Sparsity and Parameter Tying for Deep Learning using Ordered Weighted L1 Regularization", accepted to SSP 2018