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)

Transformed Schatten-1 Iterative Thresholding Algorithms for Matrix Rank Minimization and Applications. - Shuai Zhang 009; Penghang Yin; Jack Xin (CoRR, 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)

Minimization of ℓ1-2 for Compressed Sensing. - Penghang Yin; Yifei Lou; Qi He; Jack Xin (SIAM J. Sci. Comput., 2015)

Iterative ℓ1 minimization for non-convex compressed sensing. - Penghang Yin; Jack Xin (CoRR, 2016)

Training Ternary Neural Networks with Exact Proximal Operator. - Penghang Yin; Shuai Zhang 009; Jack Xin; Yingyong Qi (CoRR, 2016)

Point Source Super-resolution Via Non-convex L1 Based Methods. - Yifei Lou; Penghang Yin; Jack Xin (J. Sci. Comput., 2016)

A geometric blind source separation method based on facet component analysis. - Penghang Yin; Yuanchang Sun; Jack Xin (Signal Image Video Process., 2016)

Link Flow Correction For Inconsistent Traffic Flow Data Via 𝓁1-Minimization. - Penghang Yin; Zhe Sun; Wenlong Jin; Jack Xin (CoRR, 2017)

Deep Learning for Real-Time Crime Forecasting and its Ternarization. - Bao Wang 001; Penghang Yin; Andrea L. Bertozzi; P. Jeffrey Brantingham; Stanley J. Osher; Jack Xin (CoRR, 2017)

Alternating direction method of multipliers with difference of convex functions. - Tao Sun 005; Penghang Yin; Lizhi Cheng; Hao Jiang 001 (Adv. Comput. Math., 2018)

Laplacian Smoothing Gradient Descent. - Stanley J. Osher; Bao Wang 001; Penghang Yin; Xiyang Luo; Minh Pham 003; Alex Tong Lin (CoRR, 2018)

Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks. - Penghang Yin; Shuai Zhang 009; Jiancheng Lyu; Stanley J. Osher; Yingyong Qi; Jack Xin (CoRR, 2018)

Adversarial Defense via Data Dependent Activation Function and Total Variation Minimization. - Bao Wang 001; Alex Tong Lin; Zuoqiang Shi; Wei Zhu 007; Penghang Yin; Andrea L. Bertozzi; Stanley J. Osher (CoRR, 2018)

Computations of Optimal Transport Distance with Fisher Information Regularization. - Wuchen Li; Penghang Yin; 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)

Stochastic Backward Euler: An Implicit Gradient Descent Algorithm for k-Means Clustering. - Penghang Yin; Minh Pham 003; Adam M. Oberman; Stanley J. Osher (J. Sci. Comput., 2018)

Linear Feature Transform and Enhancement of Classification on Deep Neural Network. - Penghang Yin; Jack Xin; Yingyong Qi (J. Sci. Comput., 2018)

BinaryRelax: A Relaxation Approach for Training Deep Neural Networks with Quantized Weights. - Penghang Yin; Shuai Zhang 009; Jiancheng Lyu; Stanley J. Osher; Yingyong Qi; Jack Xin (SIAM J. Imaging Sci., 2018)

Non-Ergodic Convergence Analysis of Heavy-Ball Algorithms. - Tao Sun 005; Penghang Yin; Dongsheng Li 001; Chun Huang; Lei Guan; Hao Jiang 001 (AAAI, 2019)

Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets. - Penghang Yin; Jiancheng Lyu; Shuai Zhang 009; Stanley J. Osher; Yingyong Qi; Jack Xin (ICLR (Poster), 2019)

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)

Learning Quantized Neural Nets by Coarse Gradient Method for Non-linear Classification. - Ziang Long; Penghang Yin; Jack Xin (CoRR, 2020)

Recurrence of Optimum for Training Weight and Activation Quantized Networks. - Ziang Long; Penghang Yin; Jack Xin (CoRR, 2020)

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)

MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization. - Aozhong Zhang; Naigang Wang; Yanxia Deng; Xin Li; Zi Yang; Penghang Yin (NeurIPS, 2024)

COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization. - Aozhong Zhang; Zi Yang; Naigang Wang; Yingyong Qin; Jack Xin; Xin Li 005; Penghang Yin (CoRR, 2024)

MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization. - Aozhong Zhang; Naigang Wang; Yanxia Deng; Xin Li 005; Zi Yang; Penghang Yin (CoRR, 2024)

Two-Step Quadratic Programming for Physically Meaningful Smoothing of Longitudinal Vehicle Trajectories. - Ximeng Fan; Wen-Long Jin; Penghang Yin (Transp. Sci., 2024)

COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization. - Aozhong Zhang; Zi Yang; Naigang Wang; Yingyong Qi; Jack Xin; Xin Li 005; Penghang Yin (IEEE Access, 2025)

CLoQ: Enhancing Fine-Tuning of Quantized LLMs via Calibrated LoRA Initialization. - Yanxia Deng; Aozhong Zhang; Naigang Wang; Selcuk Gurses; Zi Yang; Penghang Yin (CoRR, 2025)

Beyond Discreteness: Finite-Sample Analysis of Straight-Through Estimator for Quantization. - Halyun Jeong; Jack Xin; Penghang Yin (CoRR, 2025)

DiaBlo: Diagonal Blocks Are Sufficient For Finetuning. - Selcuk Gurses; Aozhong Zhang; Yanxia Deng; Xun Dong; Xin Li 005; Naigang Wang; Penghang Yin; Zi Yang (CoRR, 2025)