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A penalized two-pass regression to predict stock returns with time-varying risk premia
We develop a penalized two-pass regression with time-varying factor loadings.
Multi-Signal Approaches for Repeated Sampling Schemes in Inertial Sensor Calibration
While different techniques are available to model and remove the deterministic errors, there has been considerable research over the past years with respect to modelling the stochastic errors which have complex structures.
SWAG: A Wrapper Method for Sparse Learning
As a consequence, there is the need to make the outputs of machine learning algorithms more interpretable and to deliver a library of "equivalent" learners (in terms of prediction performance) that users can select based on attribute availability in order to test and/or make use of these learners for predictive/diagnostic purposes.
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