363 citations · 989 across the 32 of their papers we have counts for
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Prediction Sets for High-Dimensional Mixture of Experts Models
Adel Javanmard, Simeng Shao, Jacob Bien
Large datasets make it possible to build predictive models that can capture heterogenous relationships between the response variable and features. The mixture of high-dimensional l…
Prediction Error Bounds for Linear Regression With the TREX
Jacob Bien, Irina Gaynanova, Johannes Lederer +1
The TREX is a recently introduced approach to sparse linear regression. In contrast to most well-known approaches to penalized regression, the TREX can be formulated without the us…
Learning Local Dependence In Ordered Data
Guo Yu, Jacob Bien
In many applications, data come with a natural ordering. This ordering can often induce local dependence among nearby variables. However, in complex data, the width of this depende…
Convex Banding of the Covariance Matrix
Jacob Bien, Florentina Bunea, Luo Xiao
We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which the variables have a known ordering. Our estimator, which is the solution to a con…
Strong rules for discarding predictors in lasso-type problems
Robert Tibshirani, Jacob Bien, Jerome Friedman +4
We consider rules for discarding predictors in lasso regression and related problems, for computational efficiency. El Ghaoui et al (2010) propose "SAFE" rules that guarantee that…