Generally, the present disclosure is directed to determining the cheapest datacenter for a computing task to be computed in. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict the cost of computing at a datacenter over a time interval based on time data, weather data, and/or grid statistics
We present a framework based on machine learning for reducing the problem size of a short-term hydro...
Machine learning (ML) is prevalent in today’s world. Starting from the need to improve artificial in...
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering,...
Machine learning (ML) allows computers to learn from historical data and make decisions without bein...
As increased demand of cloud computing leads to increased electricity costs for cloud providers, the...
Elastic Cloud Compute (EC2) is one of the most well-known services provided by Amazon for provisioni...
One of the most exciting tools that has entered our life in recent years is machine learning. The fa...
Since the COVID-19 pandemic, many activities are now carried out in a Work From Home (WFH) manner. A...
This research provides benchmark accuracies for forecasting of an aggregated price of the Dutch intr...
Due to the ongoing climate crisis, reducing waste and carbon emissions has become hot topic in many ...
The flourishing development of the cloud computing paradigm provides several services in the industr...
As Machine Learning is becoming more accessible to small businesses, thanks to the rapid advance in ...
Aim of this paper is to describe and compare the machine learning and deep learning based forecastin...
Cloud computing is a network of remote computing resources hosted on the Internet that allow users t...
Autonomic Computing is a Computer Science and Technologies research area, originated during mid 2000...
We present a framework based on machine learning for reducing the problem size of a short-term hydro...
Machine learning (ML) is prevalent in today’s world. Starting from the need to improve artificial in...
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering,...
Machine learning (ML) allows computers to learn from historical data and make decisions without bein...
As increased demand of cloud computing leads to increased electricity costs for cloud providers, the...
Elastic Cloud Compute (EC2) is one of the most well-known services provided by Amazon for provisioni...
One of the most exciting tools that has entered our life in recent years is machine learning. The fa...
Since the COVID-19 pandemic, many activities are now carried out in a Work From Home (WFH) manner. A...
This research provides benchmark accuracies for forecasting of an aggregated price of the Dutch intr...
Due to the ongoing climate crisis, reducing waste and carbon emissions has become hot topic in many ...
The flourishing development of the cloud computing paradigm provides several services in the industr...
As Machine Learning is becoming more accessible to small businesses, thanks to the rapid advance in ...
Aim of this paper is to describe and compare the machine learning and deep learning based forecastin...
Cloud computing is a network of remote computing resources hosted on the Internet that allow users t...
Autonomic Computing is a Computer Science and Technologies research area, originated during mid 2000...
We present a framework based on machine learning for reducing the problem size of a short-term hydro...
Machine learning (ML) is prevalent in today’s world. Starting from the need to improve artificial in...
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering,...