In ensemble learning, we average the predictions of multiple base learners (e.g. SVM + ANN + Linear regression). Instead of taking the mean of the individual base models' predictions, can lasso be used somehow to intelligently weight the individual predictions, in other words, decide that the ensemble prediction should be 45% SVM, 40% ANN and 15% linear regression? Lasso is normally used for feature selection, but isn't applying it for model selection also a technique? Source papers would be nice.
and if not lasso, how about using an optimization algorithm like particle swarm to intelligently weight the base learners' predictions instead?