output
20002025
most citedThe importance of transparency and reproducibility in artificial intelligence research

533 citations

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Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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5 papers · 1 filter

stat.ML2023★ 1 cited

DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging Data

Taehyo Kim, Hai Shu, Qiran Jia +1

Voxel-based multiple testing is widely used in neuroimaging data analysis. Traditional false discovery rate (FDR) control methods often ignore the spatial dependence among the voxe…

stat.ML2021★ 106 cited

S-LIME: Stabilized-LIME for Model Explanation

Zhengze Zhou, Giles Hooker, Fei Wang

An increasing number of machine learning models have been deployed in domains with high stakes such as finance and healthcare. Despite their superior performances, many models are…

stat.ML2020★ 17 cited

Adversarial Infidelity Learning for Model Interpretation

Jian Liang, Bing Bai, Yuren Cao +2

Model interpretation is essential in data mining and knowledge discovery. It can help understand the intrinsic model working mechanism and check if the model has undesired characte…

stat.ML2017

Statistical Inference for Data-adaptive Doubly Robust Estimators with Survival Outcomes

Iván Díaz

The consistency of doubly robust estimators relies on consistent estimation of at least one of two nuisance regression parameters. In moderate to large dimensions, the use of flexi…

stat.ML2015★ 9 cited

Model Accuracy and Runtime Tradeoff in Distributed Deep Learning:A Systematic Study

Suyog Gupta, Wei Zhang, Fei Wang

This paper presents Rudra, a parameter server based distributed computing framework tuned for training large-scale deep neural networks. Using variants of the asynchronous stochast…