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2020 – today
- 2024
[i17]Aozhong Zhang, Zi Yang, Naigang Wang, Yingyong Qin, Jack Xin, Xin Li, Penghang Yin:
COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization. CoRR abs/2403.07134 (2024)- [i16]Aozhong Zhang, Naigang Wang, Yanxia Deng, Xin Li, Zi Yang, Penghang Yin:
MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization. CoRR abs/2406.00800 (2024) - 2023
- [j12]Zhijian Li
, Biao Yang, Penghang Yin, Yingyong Qi, Jack Xin:
Feature Affinity Assisted Knowledge Distillation and Quantization of Deep Neural Networks on Label-Free Data. IEEE Access 11: 78042-78051 (2023) - [i15]Zhijian Li, Biao Yang, Penghang Yin, Yingyong Qi, Jack Xin:
Feature Affinity Assisted Knowledge Distillation and Quantization of Deep Neural Networks on Label-Free Data. CoRR abs/2302.10899 (2023) - 2020
- [i14]Ziang Long, Penghang Yin, Jack Xin:
Global Convergence and Geometric Characterization of Slow to Fast Weight Evolution in Neural Network Training for Classifying Linearly Non-Separable Data. CoRR abs/2002.12563 (2020) - [i13]Ziang Long, Penghang Yin, Jack Xin:
Learning Quantized Neural Nets by Coarse Gradient Method for Non-linear Classification. CoRR abs/2011.11256 (2020) - [i12]Ziang Long, Penghang Yin, Jack Xin:
Recurrence of Optimum for Training Weight and Activation Quantized Networks. CoRR abs/2012.05529 (2020)
2010 – 2019
- 2019
- [c2]Tao Sun, Penghang Yin, Dongsheng Li, Chun Huang, Lei Guan, Hao Jiang:
Non-Ergodic Convergence Analysis of Heavy-Ball Algorithms. AAAI 2019: 5033-5040 - [c1]Penghang Yin, Jiancheng Lyu, Shuai Zhang, Stanley J. Osher, Yingyong Qi, Jack Xin:
Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets. ICLR (Poster) 2019 - [i11]Penghang Yin, Jiancheng Lyu, Shuai Zhang, Stanley J. Osher, Yingyong Qi, Jack Xin:
Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets. CoRR abs/1903.05662 (2019) - 2018
- [j11]Tao Sun, Penghang Yin, Lizhi Cheng, Hao Jiang:
Alternating direction method of multipliers with difference of convex functions. Adv. Comput. Math. 44(3): 723-744 (2018) - [j10]Wuchen Li, Penghang Yin, Stanley J. Osher:
Computations of Optimal Transport Distance with Fisher Information Regularization. J. Sci. Comput. 75(3): 1581-1595 (2018) - [j9]Ernest K. Ryu, Wuchen Li, Penghang Yin, Stanley J. Osher:
Unbalanced and Partial L1 Monge-Kantorovich Problem: A Scalable Parallel First-Order Method. J. Sci. Comput. 75(3): 1596-1613 (2018) - [j8]Penghang Yin, Jack Xin, Yingyong Qi:
Linear Feature Transform and Enhancement of Classification on Deep Neural Network. J. Sci. Comput. 76(3): 1396-1406 (2018) - [j7]Penghang Yin, Minh Pham, Adam M. Oberman, Stanley J. Osher:
Stochastic Backward Euler: An Implicit Gradient Descent Algorithm for k-Means Clustering. J. Sci. Comput. 77(2): 1133-1146 (2018) - [j6]Penghang Yin, Shuai Zhang, Jiancheng Lyu, Stanley J. Osher, Yingyong Qi, Jack Xin:
BinaryRelax: A Relaxation Approach for Training Deep Neural Networks with Quantized Weights. SIAM J. Imaging Sci. 11(4): 2205-2223 (2018) - [i10]Penghang Yin, Shuai Zhang, Jiancheng Lyu, Stanley J. Osher, Yingyong Qi, Jack Xin:
BinaryRelax: A Relaxation Approach For Training Deep Neural Networks With Quantized Weights. CoRR abs/1801.06313 (2018) - [i9]Stanley J. Osher, Bao Wang, Penghang Yin, Xiyang Luo, Minh Pham, Alex Tong Lin:
Laplacian Smoothing Gradient Descent. CoRR abs/1806.06317 (2018) - [i8]Penghang Yin, Shuai Zhang, Jiancheng Lyu, Stanley J. Osher, Yingyong Qi, Jack Xin:
Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks. CoRR abs/1808.05240 (2018) - [i7]Bao Wang, Alex Tong Lin, Zuoqiang Shi, Wei Zhu, Penghang Yin, Andrea L. Bertozzi, Stanley J. Osher:
Adversarial Defense via Data Dependent Activation Function and Total Variation Minimization. CoRR abs/1809.08516 (2018) - 2017
- [i6]Penghang Yin, Zhe Sun, Wenlong Jin, Jack Xin:
Link Flow Correction For Inconsistent Traffic Flow Data Via 𝓁1-Minimization. CoRR abs/1704.02052 (2017) - [i5]Penghang Yin, Minh Pham, Adam M. Oberman, Stanley J. Osher:
Stochastic Backward Euler: An Implicit Gradient Descent Algorithm for k-means Clustering. CoRR abs/1710.07746 (2017) - [i4]Bao Wang, Penghang Yin, Andrea L. Bertozzi, P. Jeffrey Brantingham, Stanley J. Osher, Jack Xin:
Deep Learning for Real-Time Crime Forecasting and its Ternarization. CoRR abs/1711.08833 (2017) - 2016
- [j5]Yifei Lou, Penghang Yin, Jack Xin:
Point Source Super-resolution Via Non-convex L1 Based Methods. J. Sci. Comput. 68(3): 1082-1100 (2016) - [j4]Penghang Yin, Yuanchang Sun, Jack Xin:
A geometric blind source separation method based on facet component analysis. Signal Image Video Process. 10(1): 19-28 (2016) - [i3]Penghang Yin, Jack Xin:
Iterative ℓ1 minimization for non-convex compressed sensing. CoRR abs/1604.07924 (2016) - [i2]Penghang Yin, Shuai Zhang, Jack Xin, Yingyong Qi:
Training Ternary Neural Networks with Exact Proximal Operator. CoRR abs/1612.06052 (2016) - 2015
- [j3]Yifei Lou, Penghang Yin, Qi He, Jack Xin:
Computing Sparse Representation in a Highly Coherent Dictionary Based on Difference of L1 and L2. J. Sci. Comput. 64(1): 178-196 (2015) - [j2]Penghang Yin, Yifei Lou, Qi He, Jack Xin:
Minimization of ℓ1-2 for Compressed Sensing. SIAM J. Sci. Comput. 37(1) (2015) - [i1]Shuai Zhang, Penghang Yin, Jack Xin:
Transformed Schatten-1 Iterative Thresholding Algorithms for Matrix Rank Minimization and Applications. CoRR abs/1506.04444 (2015) - 2014
- [j1]Penghang Yin, Ernie Esser, Jack Xin:
Ratio and difference of $l_1$ and $l_2$ norms and sparse representation with coherent dictionaries. Commun. Inf. Syst. 14(2): 87-109 (2014)
Coauthor Index
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