Ping Tang

1. On Large-Batch Training for Deep Learning: Generalization Gap and Sharp\n Minima
   2016/09/15 by Nitish Shirish Keskar, Dheevatsa Mudigere, Keskar, Nitish Shirish +7 · 187 citations
   Computer Science · #Stochastic Gradient Optimization Techniques #Machine Learning and Algorithms #Machine Learning and ELM
2. The prevalence of compassion satisfaction and compassion fatigue among nurses: A systematic review and meta-analysis
   2021/05/15 by Wanqing Xie, Lingmin Chen, Fen Feng +6 · 29 citations
   Health Professions · Nursing · Psychology · #Healthcare professionals’ stress and burnout #Nursing education and management #Mindfulness and Compassion Interventions
3. Leveraging the bfloat16 Artificial Intelligence Datatype For\n Higher-Precision Computations
   2019/04/12 by Greg Henry, Henry, Greg, Ping Tang +3 · 5 citations
   Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Mathematical Software (cs.MS) #Matrix Theory and Algorithms #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Numerical Methods and Algorithms
4. A Progressive Batching L-BFGS Method for Machine Learning
   2018/02/15 by Raghu Bollapragada, Dheevatsa Mudigere, Bollapragada, Raghu +7 · 3 citations
   Computer Science · Engineering · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Machine Learning and Algorithms
5. Surface Ferron Excitations in Ferroelectrics and Their Directional Routing
   2022/12/02 by Xi-Han Zhou, Zhou, Xi-Han, Cai, Chengyuan +10 · 3 citations
   Engineering · Physics and Astronomy · #Characterization and Applications of Magnetic Nanoparticles #FOS: Physical sciences #Magnetic Field Sensors Techniques #Magnetic properties of thin films #Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
6. Sparse Coding by Spiking Neural Networks: Convergence Theory and Computational Results
   2017/05/15 by Ping Tang, Tsung-Han Lin, Tang, Ping Tak Peter +3 · 2 citations
   Computer Science · Engineering · Neuroscience · #Advanced Memory and Neural Computing #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE) #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #Numerical Analysis (math.NA)
7. Faster CNNs with Direct Sparse Convolutions and Guided Pruning
   2016/08/04 by Jongsoo Park, Sheng Li, Park, Jongsoo +11 · 1 citation
   Computer Science · Engineering · #Advanced Image and Video Retrieval Techniques #Advanced Neural Network Applications #Advanced SAR Imaging Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
8. Electric Analog of Magnons in Order-Disorder Ferroelectrics
   2023/09/07 by Ping Tang, G. Bauer, Tang, Ping +1 · 3 citations
   Physics and Astronomy · #FOS: Physical sciences #Magnetic properties of thin films #Materials Science (cond-mat.mtrl-sci) #Quantum and electron transport phenomena #Topological Materials and Phenomena
9. Enabling Sparse Winograd Convolution by Native Pruning
   2017/02/28 by Sheng R. Li, Li, Sheng, Jongsoo Park +3 · 1 citation
   Computer Science · #Advanced Neural Network Applications #Advanced Vision and Imaging #Image Enhancement Techniques