An Empirical Study towards Characterizing Deep Learning Development and
Deployment across Different Frameworks and Platforms

An Empirical Study towards Characterizing Deep Learning Development and Deployment across Different Frameworks and Platforms

15 September 2019

Yang Liu

Papers citing "An Empirical Study towards Characterizing Deep Learning Development and Deployment across Different Frameworks and Platforms"

16 / 16 papers shown

Title
Studying the Impact of TensorFlow and PyTorch Bindings on Machine Learning Software Quality Hao Li Gopi Krishnan Rajbahadur C. Bezemer 39 5 0 07 Jul 2024
Quality at the Tail of Machine Learning Inference Zhengxin Yang Wanling Gao Chunjie Luo Lei Wang Fei Tang Xu Wen Jianfeng Zhan 38 1 0 25 Dec 2022
An Empirical Study of Challenges in Converting Deep Learning Models Moses Openja Amin Nikanjam Ahmed Haj Yahmed Foutse Khomh Zhen Ming Zhengyong Jiang AAML 31 19 0 28 Jun 2022
Characterizing and Understanding the Behavior of Quantized Models for Reliable Deployment Qiang Hu Yuejun Guo Maxime Cordy Xiaofei Xie Wei Ma Mike Papadakis Yves Le Traon MQ 41 1 0 08 Apr 2022
Towards Training Reproducible Deep Learning Models Boyuan Chen Mingzhi Wen Yong Shi Dayi Lin Gopi Krishnan Rajbahadur Zhen Ming Z. Jiang SyDa 15 37 0 04 Feb 2022
Security for Machine Learning-based Software Systems: a survey of threats, practices and challenges Huaming Chen Muhammad Ali Babar AAML 37 21 0 12 Jan 2022
Understanding Performance Problems in Deep Learning Systems Junming Cao Bihuan Chen Chao Sun Longjie Hu Shuai Wu Xin Peng 30 27 0 03 Dec 2021
Smart at what cost? Characterising Mobile Deep Neural Networks in the wild Mario Almeida Stefanos Laskaridis Abhinav Mehrotra L. Dudziak Ilias Leontiadis Nicholas D. Lane HAI 112 44 0 28 Sep 2021
Which Design Decisions in AI-enabled Mobile Applications Contribute to Greener AI? Roger Creus Castanyer Silverio Martínez-Fernández Xavier Franch 40 11 0 28 Sep 2021
Integration of Convolutional Neural Networks in Mobile Applications Roger Creus Castanyer Silverio Martínez-Fernández Xavier Franch 21 12 0 11 Mar 2021
A Software Engineering Perspective on Engineering Machine Learning Systems: State of the Art and Challenges G. Giray 33 120 0 14 Dec 2020
Software engineering for artificial intelligence and machine learning software: A systematic literature review E. Nascimento Anh Nguyen-Duc Ingrid Sundbø T. Conte 8 40 0 07 Nov 2020
A Performance-Sensitive Malware Detection System Using Deep Learning on Mobile Devices Ruitao Feng Sen Chen Xiaofei Xie Guozhu Meng Shang-Wei Lin Yang Liu 36 103 0 11 May 2020
Towards Characterizing Adversarial Defects of Deep Learning Software from the Lens of Uncertainty Xiyue Zhang Xiaofei Xie Lei Ma Xiaoning Du Q. Hu Yang Liu Jianjun Zhao Meng Sun AAML 13 76 0 24 Apr 2020
CORE: Automating Review Recommendation for Code Changes J. Siow Cuiyun Gao Lingling Fan Sen Chen Yang Liu 14 55 0 20 Dec 2019
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 249 1,838 0 03 Feb 2017