104 citations · 299 across the 16 of their papers we have counts for
4 papers · 1 filter
Optimizing accuracy and diversity: a multi-task approach to forecast combinations
Giovanni Felici, Antonio M. Sudoso
We present a multi-task optimization approach based on a deep learning architecture for time series forecasting. We leverage large collections of time series to identify the weight…
Predicting municipalities in financial distress: a machine learning approach enhanced by domain expertise
Dario Piermarini, Antonio M. Sudoso, Veronica Piccialli
Financial distress of municipalities, although comparable to bankruptcy of private companies, has a far more serious impact on the well-being of communities. For this reason, it is…
A machine learning approach for forecasting hierarchical time series
Paolo Mancuso, Veronica Piccialli, Antonio M. Sudoso
In this paper, we propose a machine learning approach for forecasting hierarchical time series. When dealing with hierarchical time series, apart from generating accurate forecasts…
Improving Non-Intrusive Load Disaggregation through an Attention-Based Deep Neural Network
Veronica Piccialli, Antonio M. Sudoso
Energy disaggregation, known in the literature as Non-Intrusive Load Monitoring (NILM), is the task of inferring the power demand of the individual appliances given the aggregate p…