Computer Systems Have 99 Problems, Let's Not Make Machine Learning Another One

11/28/2019
by   David Mohaisen, et al.
0

Machine learning techniques are finding many applications in computer systems, including many tasks that require decision making: network optimization, quality of service assurance, and security. We believe machine learning systems are here to stay, and to materialize on their potential we advocate a fresh look at various key issues that need further attention, including security as a requirement and system complexity, and how machine learning systems affect them. We also discuss reproducibility as a key requirement for sustainable machine learning systems, and leads to pursuing it.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/01/2019

Open Problems in Engineering Machine Learning Systems and the Quality Model

Fatal accidents are a major issue hindering the wide acceptance of safet...
research
03/24/2023

An investigation of licensing of datasets for machine learning based on the GQM model

Dataset licensing is currently an issue in the development of machine le...
research
12/16/2022

An Efficient Framework for Monitoring Subgroup Performance of Machine Learning Systems

Monitoring machine learning systems post deployment is critical to ensur...
research
12/05/2022

Continual learning on deployment pipelines for Machine Learning Systems

Following the development of digitization, a growing number of large Ori...
research
04/08/2021

Classification, Slippage, Failure and Discovery

This text argues for the potential of machine learning infused classific...
research
10/11/2021

Designing off-sample performance metrics

Modern machine learning systems are traditionally designed and tested wi...
research
06/05/2019

Risks from Learned Optimization in Advanced Machine Learning Systems

We analyze the type of learned optimization that occurs when a learned m...

Please sign up or login with your details

Forgot password? Click here to reset