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Hierarchical Ensemble-Based Feature Selection for Time Series Forecasting
This hierarchical structure allows for flexible depth and feature selection.
Hybrid State Space-based Learning for Sequential Data Prediction with Joint Optimization
We achieve this by introducing novel state space representations for the base models, which are then combined to provide a full state space representation of the hybrid or the ensemble.
A Hybrid Framework for Sequential Data Prediction with End-to-End Optimization
We investigate nonlinear prediction in an online setting and introduce a hybrid model that effectively mitigates, via an end-to-end architecture, the need for hand-designed features and manual model selection issues of conventional nonlinear prediction/regression methods.
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