Lasso is a widely used regression technique to find sparse representations. When the dimension of the feature space and the number of samples are extremely large, solving the Lasso problem remains challenging. To improve the efficiency of solving large-scale Lasso problems, El Ghaoui and his colleagues have proposed the SAFE rules which are able to quickly identify the inactive predictors, i.e....

This paper deals with model selection and forecasting in vector autoregressions (VARs) in situations where the set of available predictors is inconveniently large to accommodate with methods and diagnostics used in traditional small-scale models. Available information over this large dataset can be summarized into a considerably smaller set of variables through factors estimated by the dynamic ...

In what case do you like reading so much? What about the type of the trace based post silicon validation for vlsi circuits book? The needs to read? Well, everybody has their own reason why should read some books. Mostly, it will relate to their necessity to get knowledge from the book and want to read just to get entertainment. Novels, story book, and other entertaining books become so popular ...