Challenges in Deploying and monitoring Machine Learning Systems
NeurIPS VIRTUAL Workshop
Friday, 9th of December 2022
The goal of this event is to bring together people from different communities with the common interest in the Deployment of Machine Learning Systems.
With the dramatic rise of companies dedicated to providing Machine Learning software-as-a-service tools, Machine Learning has become a tool for solving real world problems that is increasingly more accessible in many industrial and social sectors. With the growth in number of deployments, also grows the number of known challenges and hurdles that practitioners face along the deployment process to ensure the continual delivery of good performance from deployed Machine Learning systems. Such challenges can lie in adoption of ML algorithms to concrete use cases, discovery and quality of data, maintenance of production ML systems, as well as ethics.
INVITED SPEAKERS
Data Science Africa, Kampala
“Lessons from the deployment of data science during the COVID-19 response in Africa"
Trinity College, Dublin
“Reinforcement learning in large-scale heterogeneous dynamic systems”
PANEL DISCUSSION ON OPEN PROBLEMS IN MACHINE LEARNING SYSTEMS
Chaired by Stephen Roberts, University of Oxford
PANEL DISCUSSION ON SECURITY AND PRIVACY IN ML SYSTEMS
Chaired by Borja Balle, DeepMind
Workshop organizers
Alessandra Tosi, Mind Foundry
Andrei Paleyes, University of Cambridge
Christian Cabrera, University of Cambridge
Fariba Yousefi, AstraZeneca
Stephen Roberts, University of Oxford
Program committee
Alberto Castagna, Arie Van Deursen, Babatunji Omoniwa, Eric Meissner, Fabio Calefato, Filippo Lanubile, Jati Husen, Luigi Quaranta, Markus Kaiser, Mohit Garg, Nicolás Cardozo, Nikolay Burlutskiy, Petra Heck, Pierre Thodoroff, Sami Alabed, Sherif Akoush, Zhenwen Dai
Contact
dmml.neurips.2022 [at] protonmail [dot] com
Previous editions: ICML 2020 Workshop, ICML 2021 Workshop