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Deconstructing Generative Adversarial Networks


Jan 27, 2019
Banghua Zhu, Jiantao Jiao, David Tse


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Generalizable Adversarial Training via Spectral Normalization


Nov 19, 2018
Farzan Farnia, Jesse M. Zhang, David Tse


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A Convex Duality Framework for GANs


Oct 28, 2018
Farzan Farnia, David Tse


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Understanding GANs: the LQG Setting


Oct 22, 2018
Soheil Feizi, Farzan Farnia, Tony Ginart, David Tse


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Hidden Hamiltonian Cycle Recovery via Linear Programming


Apr 15, 2018
Vivek Bagaria, Jian Ding, David Tse, Yihong Wu, Jiaming Xu


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NeuralFDR: Learning Discovery Thresholds from Hypothesis Features


Nov 18, 2017
Fei Xia, Martin J. Zhang, James Zou, David Tse


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Medoids in almost linear time via multi-armed bandits


Nov 07, 2017
Vivek Bagaria, Govinda M. Kamath, Vasilis Ntranos, Martin J. Zhang, David Tse


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Porcupine Neural Networks: (Almost) All Local Optima are Global


Oct 05, 2017
Soheil Feizi, Hamid Javadi, Jesse Zhang, David Tse


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A Minimax Approach to Supervised Learning


Jul 04, 2017
Farzan Farnia, David Tse


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Time-Sensitive Bandit Learning and Satisficing Thompson Sampling


Apr 28, 2017
Daniel Russo, David Tse, Benjamin Van Roy


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Maximally Correlated Principal Component Analysis


Feb 21, 2017
Soheil Feizi, David Tse

* 35 pages, 5 figures 

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Community Recovery in Graphs with Locality


Jun 01, 2016
Yuxin Chen, Govinda Kamath, Changho Suh, David Tse

* accepted in part to International Conference on Machine Learning (ICML), 2016 

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Discrete Rényi Classifiers


Nov 05, 2015
Meisam Razaviyayn, Farzan Farnia, David Tse


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