3 citations · 5 across the 6 of their papers we have counts for
6 papers
An AutoML Framework using AutoGluonTS for Forecasting Seasonal Extreme Temperatures
Pablo Rodríguez-Bocca, Guillermo Pereira, Diego Kiedanski +3
In recent years, great progress has been made in the field of forecasting meteorological variables. Recently, deep learning architectures have made a major breakthrough in forecast…
Robust and Resource-efficient Machine Learning Aided Viewport Prediction in Virtual Reality
Yuang Jiang, Konstantinos Poularakis, Diego Kiedanski +2
360-degree panoramic videos have gained considerable attention in recent years due to the rapid development of head-mounted displays (HMDs) and panoramic cameras. One major problem…
Identification of medical devices using machine learning on distribution feeder data for informing power outage response
Paraskevi Kourtza, Maitreyee Marathe, Anuj Shetty +1
Power outages caused by extreme weather events due to climate change have doubled in the United States in the last two decades. Outages pose severe health risks to over 4.4 million…
Coalitional Game-Theoretical Approach to Coinvestment with Application to Edge Computing
Rosario Patanè, Andrea Araldo, Tijani Chahed +2
We propose in this paper a coinvestment plan between several stakeholders of different types, namely a physical network owner, operating network nodes, e.g. a network operator or a…
An Overview of the Data-Loader Landscape: Comparative Performance Analysis
Iason Ofeidis, Diego Kiedanski, Leandros Tassiulas
Dataloaders, in charge of moving data from storage into GPUs while training machine learning models, might hold the key to drastically improving the performance of training jobs. R…
Energy storage applications for low voltage consumers in Uruguay
Md Umar Hashmi, Jose Horta, Diego Kiedanski +2
Energy storage can be used for many applications in the Smart Grid such as energy arbitrage, peak demand shaving, power factor correction, energy backup to name a few, and can play…