Computer Science
4 years ago

New method balances model complexity for powerful predictive accuracy

IEEE Transactions on Information Theory
On Statistical Efficiency in Learning
Jie Ding, Enmao Diao, Jiawei Zhou, Vahid Tarokh

Paper Summary

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The article discusses how to choose the best model for predicting outcomes in statistical learning. By balancing model complexity and fitting, the researchers developed a method that can predict outcomes as well as the best possible model. This method is efficient and can be used for various types of models and data. The researchers also created an online algorithm for streaming data that improves model selection and reduces computation time. Experimental studies show that this method is effective and costs less to use than other popular methods.