Penghang Yin

According to our database, Penghang Yin authored at least 28 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Two-Step Quadratic Programming for Physically Meaningful Smoothing of Longitudinal Vehicle Trajectories.

Ximeng Fan, Wen-Long Jin, Penghang Yin

Transp. Sci., 2024

MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization.

Aozhong Zhang, Naigang Wang, Yanxia Deng, Xin Li, Zi Yang, Penghang Yin

CoRR, 2024

COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization.

Aozhong Zhang, Zi Yang, Naigang Wang, Yingyong Qin, Jack Xin, Xin Li, Penghang Yin

CoRR, 2024

2023

Feature Affinity Assisted Knowledge Distillation and Quantization of Deep Neural Networks on Label-Free Data.

Zhijian Li, Biao Yang, Penghang Yin, Yingyong Qi, Jack Xin

IEEE Access, 2023

2020

Recurrence of Optimum for Training Weight and Activation Quantized Networks.

Ziang Long, Penghang Yin, Jack Xin

CoRR, 2020

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

Ziang Long, Penghang Yin, Jack Xin

CoRR, 2020

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

Ziang Long, Penghang Yin, Jack Xin

CoRR, 2020

2019

Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets.

Penghang Yin, Jiancheng Lyu, Shuai Zhang, Stanley J. Osher, Yingyong Qi, Jack Xin

Proceedings of the 7th International Conference on Learning Representations, 2019

Non-Ergodic Convergence Analysis of Heavy-Ball Algorithms.

Tao Sun, Penghang Yin, Dongsheng Li, Chun Huang, Lei Guan, Hao Jiang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

BinaryRelax: A Relaxation Approach for Training Deep Neural Networks with Quantized Weights.

Penghang Yin, Shuai Zhang, Jiancheng Lyu, Stanley J. Osher, Yingyong Qi, Jack Xin

SIAM J. Imaging Sci., 2018

Linear Feature Transform and Enhancement of Classification on Deep Neural Network.

Penghang Yin, Jack Xin, Yingyong Qi

J. Sci. Comput., 2018

Stochastic Backward Euler: An Implicit Gradient Descent Algorithm for k-Means Clustering.

Penghang Yin, Minh Pham, Adam M. Oberman, Stanley J. Osher

J. Sci. Comput., 2018

Unbalanced and Partial L₁ Monge-Kantorovich Problem: A Scalable Parallel First-Order Method.

Ernest K. Ryu, Wuchen Li, Penghang Yin, Stanley J. Osher

J. Sci. Comput., 2018

Computations of Optimal Transport Distance with Fisher Information Regularization.

Wuchen Li, Penghang Yin, Stanley J. Osher

J. Sci. Comput., 2018

Adversarial Defense via Data Dependent Activation Function and Total Variation Minimization.

Bao Wang, Alex Tong Lin, Zuoqiang Shi, Wei Zhu, Penghang Yin, Andrea L. Bertozzi, Stanley J. Osher

CoRR, 2018

Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks.

Penghang Yin, Shuai Zhang, Jiancheng Lyu, Stanley J. Osher, Yingyong Qi, Jack Xin

CoRR, 2018

Laplacian Smoothing Gradient Descent.

Stanley J. Osher, Bao Wang, Penghang Yin, Xiyang Luo, Minh Pham, Alex Tong Lin

CoRR, 2018

Alternating direction method of multipliers with difference of convex functions.

Tao Sun, Penghang Yin, Lizhi Cheng, Hao Jiang

Adv. Comput. Math., 2018

2017

Deep Learning for Real-Time Crime Forecasting and its Ternarization.

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

CoRR, 2017

Link Flow Correction For Inconsistent Traffic Flow Data Via 𝓁₁-Minimization.

Penghang Yin, Zhe Sun, Wenlong Jin, Jack Xin

CoRR, 2017

2016

A geometric blind source separation method based on facet component analysis.

Penghang Yin, Yuanchang Sun, Jack Xin

Signal Image Video Process., 2016

Point Source Super-resolution Via Non-convex L₁ Based Methods.

Yifei Lou, Penghang Yin, Jack Xin

J. Sci. Comput., 2016

Training Ternary Neural Networks with Exact Proximal Operator.

Penghang Yin, Shuai Zhang, Jack Xin, Yingyong Qi

CoRR, 2016

Iterative ℓ₁ minimization for non-convex compressed sensing.

Penghang Yin, Jack Xin

CoRR, 2016

2015

Minimization of ℓ_1-2 for Compressed Sensing.

Penghang Yin, Yifei Lou, Qi He, Jack Xin

SIAM J. Sci. Comput., 2015

Computing Sparse Representation in a Highly Coherent Dictionary Based on Difference of L₁ and L₂.

Yifei Lou, Penghang Yin, Qi He, Jack Xin

J. Sci. Comput., 2015

Transformed Schatten-1 Iterative Thresholding Algorithms for Matrix Rank Minimization and Applications.

Shuai Zhang, Penghang Yin, Jack Xin

CoRR, 2015

2014

Ratio and difference of $l_1$ and $l_2$ norms and sparse representation with coherent dictionaries.

Penghang Yin, Ernie Esser, Jack Xin

Commun. Inf. Syst., 2014