Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment

1 March 2019

Papers citing "Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment"

9 / 9 papers shown

Title
Design Patterns for AI-based Systems: A Multivocal Literature Review and Pattern Repository Lukas Heiland Marius Hauser Justus Bogner AI4TS 39 8 0 23 Mar 2023
Enabling Reproducibility and Meta-learning Through a Lifelong Database of Experiments (LDE) Jason Tsay A. Bartezzaghi Aleke Nolte C. Malossi 24 0 0 22 Feb 2022
On Continuous Integration / Continuous Delivery for Automated Deployment of Machine Learning Models using MLOps Satvik Garg Pradyumn Pundir Geetanjali Rathee P. K. Gupta Somya Garg Saransh Ahlawat VLM 4 54 0 07 Feb 2022
A Data Quality-Driven View of MLOps Cédric Renggli Luka Rimanic Nezihe Merve Gürel Bojan Karlavs Wentao Wu Ce Zhang AI4TS 22 65 0 15 Feb 2021
Machine Learning Systems in the IoT: Trustworthiness Trade-offs for Edge Intelligence Wiebke Toussaint Aaron Yi Ding 35 11 0 01 Dec 2020
Software engineering for artificial intelligence and machine learning software: A systematic literature review E. Nascimento Anh Nguyen-Duc Ingrid Sundbø T. Conte 18 40 0 07 Nov 2020
Model Assertions for Monitoring and Improving ML Models Daniel Kang Deepti Raghavan Peter Bailis Matei A. Zaharia 11 58 0 03 Mar 2020
FLAML: A Fast and Lightweight AutoML Library Chi Wang Qingyun Wu Markus Weimer Erkang Zhu 30 196 0 12 Nov 2019
Studying Software Engineering Patterns for Designing Machine Learning Systems Hironori Washizaki Hiromu Uchida Foutse Khomh Yann-Gaël Guéhéneuc 21 77 0 10 Oct 2019