Tackling climate change with machine learning
Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
Machine learning for science and society
C Rudin, KL Wagstaff - Machine Learning, 2014 - Springer
The special issue on “Machine Learning for Science and Society” showcases machine
learning work with influence on our current and future society. These papers address …
learning work with influence on our current and future society. These papers address …
Towards the systematic reporting of the energy and carbon footprints of machine learning
Accurate reporting of energy and carbon usage is essential for understanding the potential
climate impacts of machine learning research. We introduce a framework that makes this …
climate impacts of machine learning research. We introduce a framework that makes this …
Machine learning for a sustainable energy future
Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it
demands advances—at the materials, devices and systems levels—for the efficient …
demands advances—at the materials, devices and systems levels—for the efficient …
Machine learning: new ideas and tools in environmental science and engineering
The rapid increase in both the quantity and complexity of data that are being generated daily
in the field of environmental science and engineering (ESE) demands accompanied …
in the field of environmental science and engineering (ESE) demands accompanied …
The carbon footprint of machine learning training will plateau, then shrink
Machine learning (ML) workloads have rapidly grown, raising concerns about their carbon
footprint. We show four best practices to reduce ML training energy and carbon dioxide …
footprint. We show four best practices to reduce ML training energy and carbon dioxide …
Quantifying the carbon emissions of machine learning
From an environmental standpoint, there are a few crucial aspects of training a neural
network that have a major impact on the quantity of carbon that it emits. These factors …
network that have a major impact on the quantity of carbon that it emits. These factors …
Machine learning that matters
K Wagstaff - arXiv preprint arXiv:1206.4656, 2012 - arxiv.org
Much of current machine learning (ML) research has lost its connection to problems of
import to the larger world of science and society. From this perspective, there exist glaring …
import to the larger world of science and society. From this perspective, there exist glaring …
Machine learning for the geosciences: Challenges and opportunities
Geosciences is a field of great societal relevance that requires solutions to several urgent
problems facing our humanity and the planet. As geosciences enters the era of big data …
problems facing our humanity and the planet. As geosciences enters the era of big data …
[图书][B] Real-world machine learning
H Brink, J Richards, M Fetherolf - 2016 - books.google.com
Summary Real-World Machine Learning is a practical guide designed to teach working
developers the art of ML project execution. Without overdosing you on academic theory and …
developers the art of ML project execution. Without overdosing you on academic theory and …