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Generalized Information Criteria for Structured Sparse Models
We obtain non-asymptotic model selection bounds and sufficient conditions for model selection consistency of the GIC.
Machine Learning Advances for Time Series Forecasting
In this paper we survey the most recent advances in supervised machine learning and high-dimensional models for time series forecasting.
Regularized Estimation of High-Dimensional Vector AutoRegressions with Weakly Dependent Innovations
There has been considerable advance in understanding the properties of sparse regularization procedures in high-dimensional models.
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