77 citations · 81 across the 7 of their papers we have counts for
5 papers · 1 filter
Model Compression for Dynamic Forecast Combination
Vitor Cerqueira, Luis Torgo, Carlos Soares +1
The predictive advantage of combining several different predictive models is widely accepted. Particularly in time series forecasting problems, this combination is often dynamic to…
Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health Episodes
Vitor Cerqueira, Luis Torgo, Carlos Soares
The early detection of anomalous events in time series data is essential in many domains of application. In this paper we deal with critical health events, which represent a signif…
VEST: Automatic Feature Engineering for Forecasting
Vitor Cerqueira, Nuno Moniz, Carlos Soares
Time series forecasting is a challenging task with applications in a wide range of domains. Auto-regression is one of the most common approaches to address these problems. Accordin…
Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters
Vitor Cerqueira, Luis Torgo, Carlos Soares
Time series forecasting is one of the most active research topics. Machine learning methods have been increasingly adopted to solve these predictive tasks. However, in a recent wor…
autoBagging: Learning to Rank Bagging Workflows with Metalearning
Fábio Pinto, Vítor Cerqueira, Carlos Soares +1
Machine Learning (ML) has been successfully applied to a wide range of domains and applications. One of the techniques behind most of these successful applications is Ensemble Lear…