activity
20182022
most citedPrediction and outlier detection in classification problems

5 citations · 6 across the 2 of their papers we have counts for

collaborators

6 papers

stat.ME20221 cited

-norm constrained multi-block sparse canonical correlation analysis via proximal gradient descent

Leying Guan

Multi-block CCA constructs linear relationships explaining coherent variations across multiple blocks of data. We view the multi-block CCA problem as finding leading generalized ei…

math.ST2019

Conformal prediction with localization

Leying Guan

We propose a new method called localized conformal prediction, where we can perform conformal inference using only a local region around a new test sample to construct its confiden…

stat.ME20195 cited

Prediction and outlier detection in classification problems

Leying Guan, Rob Tibshirani

We consider the multi-class classification problem when the training data and the out-of-sample test data may have different distributions and propose a method called BCOPS (balanc…

stat.ME2018

Detecting strong signals in gene perturbation experiments: An adaptive approach with power guarantee and FDR control

Leying Guan, Xi Chen, Wing Hung Wong

The perturbation of a transcription factor should affect the expression levels of its direct targets. However, not all genes showing changes in expression are direct targets. To in…

stat.ME2018

Post model-fitting exploration via a "Next-Door" analysis

Leying Guan, Robert Tibshirani

We propose a simple method for evaluating the model that has been chosen by an adaptive regression procedure, our main focus being the lasso. This procedure deletes each chosen pre…

stat.ME2018

Test Error Estimation after Model Selection Using Validation Error

Leying Guan

When performing supervised learning with the model selected using validation error from sample splitting and cross validation, the minimum value of the validation error can be bias…