Search Results for author:
Found 7 papers, 3 papers with code
AdaPT-GMM: Powerful and robust covariate-assisted multiple testing
We propose a new empirical Bayes method for covariate-assisted multiple testing with false discovery rate (FDR) control, where we model the local false discovery rate for each hypothesis as a function of both its covariates and p-value.
Statistical Methods for Replicability Assessment
Large-scale replication studies like the Reproducibility Project: Psychology (RP:P) provide invaluable systematic data on scientific replicability, but most analyses and interpretations of the data fail to agree on the definition of "replicability" and disentangle the inexorable consequences of known selection bias from competing explanations.
Methodology Applications 62F03, 62P25
Data Augmentation via Levy Processes
The framework imagines data as being drawn from a slice of a Levy process.
Selective Sequential Model Selection
Extending the selected-model tests of Fithian et al. (2014), we construct p-values for each step in the path which account for the adaptive selection of the model path using the data.
Altitude Training: Strong Bounds for Single-Layer Dropout
Dropout training, originally designed for deep neural networks, has been successful on high-dimensional single-layer natural language tasks.
Flexible Low-Rank Statistical Modeling with Side Information
We propose a general framework for reduced-rank modeling of matrix-valued data.
Local case-control sampling: Efficient subsampling in imbalanced data sets
By contrast, our estimator is consistent for $\theta^*$ provided that the pilot estimate is.
