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Neural Networks with Recurrent Generative Feedback

Jul 17, 2020
Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan Nguyen, Doris Y. Tsao, Anima Anandkumar

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Sample Efficient Graph-Based Optimization with Noisy Observations

Jun 04, 2020
Tan Nguyen, Ali Shameli, Yasin Abbasi-Yadkori, Anup Rao, Branislav Kveton

* AISTATS 2019 
* The first version of this paper appeared in AISTATS 2019. Thank to community feedback, some typos and a minor issue have been identified. Specifically, on page 4, column 2, line 18, the statement $\Delta_{1,s} \ge (1+m)^{S-1-s} \Delta_1$ is not valid, and in the proof of Theorem 2, "By Lemma 1" should be "By Definition 2". These problems are fixed in this updated version published here on arxiv 

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Learning Near-optimal Convex Combinations of Basis Models with Generalization Guarantees

Oct 09, 2019
Tan Nguyen, Nan Ye, Peter L. Bartlett

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Dual Dynamic Inference: Enabling More Efficient, Adaptive and Controllable Deep Inference

Jul 17, 2019
Yue Wang, Jianghao Shen, Ting-Kuei Hu, Pengfei Xu, Tan Nguyen, Richard Baraniuk, Zhangyang Wang, Yingyan Lin

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Out-of-Distribution Detection Using Neural Rendering Generative Models

Jul 10, 2019
Yujia Huang, Sihui Dai, Tan Nguyen, Richard G. Baraniuk, Anima Anandkumar

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Semi-Supervised Learning with the Deep Rendering Mixture Model

Dec 06, 2016
Tan Nguyen, Wanjia Liu, Ethan Perez, Richard G. Baraniuk, Ankit B. Patel

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A Probabilistic Framework for Deep Learning

Dec 06, 2016
Ankit B. Patel, Tan Nguyen, Richard G. Baraniuk

* arXiv admin note: substantial text overlap with arXiv:1504.00641 

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A Probabilistic Theory of Deep Learning

Apr 02, 2015
Ankit B. Patel, Tan Nguyen, Richard G. Baraniuk

* 56 pages, 6 figures, 2 tables 

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