34 citations · 41 across the 5 of their papers we have counts for
5 papers
On the Self-Penalization Phenomenon in Feature Selection
Michael I. Jordan, Keli Liu, Feng Ruan
We describe an implicit sparsity-inducing mechanism based on minimization over a family of kernels: \begin{equation*} \min_{β, f}~\widehat{\mathbb{E}}[L(Y, f(β^{1/q} \odot X)] + λ_…
Taming Nonconvexity in Kernel Feature Selection -- Favorable Properties of the Laplace Kernel
Feng Ruan, Keli Liu, Michael I. Jordan
Kernel-based feature selection is an important tool in nonparametric statistics. Despite many practical applications of kernel-based feature selection, there is little statistical…
A Self-Penalizing Objective Function for Scalable Interaction Detection
Keli Liu, Feng Ruan
We tackle the problem of nonparametric variable selection with a focus on discovering interactions between variables. With variables there are possible order- inter…
More powerful post-selection inference, with application to the Lasso
Keli Liu, Jelena Markovic, Robert Tibshirani
Investigators often use the data to generate interesting hypotheses and then perform inference for the generated hypotheses. P-values and confidence intervals must account for this…
There is Individualized Treatment. Why Not Individualized Inference?
Keli Liu, Xiao-Li Meng
Doctors use statistics to advance medical knowledge; we use a medical analogy to introduce statistical inference "from scratch" and to highlight an improvement. Your doctor, perhap…