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Learning Quantized Neural Nets by Coarse Gradient Method for Non-linear Classification

Nov 23, 2020
Ziang Long, Penghang Yin, Jack Xin


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A Spatial-Temporal Graph Based Hybrid Infectious Disease Model with Application to COVID-19

Oct 18, 2020
Yunling Zheng, Zhijian Li, Jack Xin, Guofa Zhou


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Nonconvex Regularization for Network Slimming:Compressing CNNs Even More

Oct 03, 2020
Kevin Bui, Fredrick Park, Shuai Zhang, Yingyong Qi, Jack Xin

* Will be published in ISVC'20 

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An Integrated Approach to Produce Robust Models with High Efficiency

Aug 31, 2020
Zhijian Li, Bao Wang, Jack Xin


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RARTS: a Relaxed Architecture Search Method

Aug 10, 2020
Fanghui Xue, Yingyong Qi, Jack Xin


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A Recurrent Neural Network and Differential Equation Based Spatiotemporal Infectious Disease Model with Application to COVID-19

Jul 14, 2020
Zhijian Li, Yunling Zheng, Jack Xin, Guofa Zhou


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A Weighted Difference of Anisotropic and Isotropic Total Variation for Relaxed Mumford-Shah Color and Multiphase Image Segmentation

May 09, 2020
Kevin Bui, Fredrick Park, Yifei Lou, Jack Xin


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Global Convergence and Geometric Characterization of Slow to Fast Weight Evolution in Neural Network Training for Classifying Linearly Non-Separable Data

Mar 05, 2020
Ziang Long, Penghang Yin, Jack Xin


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$\ell_0$ Regularized Structured Sparsity Convolutional Neural Networks

Dec 17, 2019
Kevin Bui, Fredrick Park, Shuai Zhang, Yingyong Qi, Jack Xin


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Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets

Mar 13, 2019
Penghang Yin, Jiancheng Lyu, Shuai Zhang, Stanley Osher, Yingyong Qi, Jack Xin


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Learning Sparse Neural Networks via $\ell_0$ and T$\ell_1$ by a Relaxed Variable Splitting Method with Application to Multi-scale Curve Classification

Feb 20, 2019
Fanghui Xue, Jack Xin


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A Study on Graph-Structured Recurrent Neural Networks and Sparsification with Application to Epidemic Forecasting

Feb 13, 2019
Zhijian Li, Xiyang Luo, Bao Wang, Andrea L. Bertozzi, Jack Xin


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Convergence of a Relaxed Variable Splitting Coarse Gradient Descent Method for Learning Sparse Weight Binarized Activation Neural Networks

Feb 09, 2019
Thu Dinh, Jack Xin

* arXiv admin note: substantial text overlap with arXiv:1812.05719 

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AutoShuffleNet: Learning Permutation Matrices via an Exact Lipschitz Continuous Penalty in Deep Convolutional Neural Networks

Jan 24, 2019
Jiancheng Lyu, Shuai Zhang, Yingyong Qi, Jack Xin


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BinaryRelax: A Relaxation Approach For Training Deep Neural Networks With Quantized Weights

Sep 05, 2018
Penghang Yin, Shuai Zhang, Jiancheng Lyu, Stanley Osher, Yingyong Qi, Jack Xin


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Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks

Aug 29, 2018
Penghang Yin, Shuai Zhang, Jiancheng Lyu, Stanley Osher, Yingyong Qi, Jack Xin


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Deep Learning for Real-Time Crime Forecasting and its Ternarization

Nov 23, 2017
Bao Wang, Penghang Yin, Andrea L. Bertozzi, P. Jeffrey Brantingham, Stanley J. Osher, Jack Xin

* 14 pages, 7 figures 

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Quantization and Training of Low Bit-Width Convolutional Neural Networks for Object Detection

Aug 17, 2017
Penghang Yin, Shuai Zhang, Yingyong Qi, Jack Xin


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A Method for Finding Structured Sparse Solutions to Non-negative Least Squares Problems with Applications

Jan 03, 2013
Ernie Esser, Yifei Lou, Jack Xin

* 38 pages, 14 figures 

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A convex model for non-negative matrix factorization and dimensionality reduction on physical space

Feb 04, 2011
Ernie Esser, Michael Möller, Stanley Osher, Guillermo Sapiro, Jack Xin

* 14 pages, 9 figures. EE and JX were supported by NSF grants {DMS-0911277}, {PRISM-0948247}, MM by the German Academic Exchange Service (DAAD), SO and MM by NSF grants {DMS-0835863}, {DMS-0914561}, {DMS-0914856} and ONR grant {N00014-08-1119}, and GS was supported by NSF, NGA, ONR, ARO, DARPA, and {NSSEFF.} 

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