2 citations · 3 across the 4 of their papers we have counts for
4 papers
Spectral Regularized Kernel Goodness-of-Fit Tests
Omar Hagrass, Bharath K. Sriperumbudur, Bing Li
Maximum mean discrepancy (MMD) has enjoyed a lot of success in many machine learning and statistical applications, including non-parametric hypothesis testing, because of its abili…
Spectral Regularized Kernel Two-Sample Tests
Omar Hagrass, Bharath K. Sriperumbudur, Bing Li
Over the last decade, an approach that has gained a lot of popularity to tackle nonparametric testing problems on general (i.e., non-Euclidean) domains is based on the notion of re…
Robust Estimation of Loss-Based Measures of Model Performance under Covariate Shift
Samantha Morrison, Constantine Gatsonis, Issa J. Dahabreh +2
We present methods for estimating loss-based measures of the performance of a prediction model in a target population that differs from the source population in which the model was…
B-scaling: A Novel Nonparametric Data Fusion Method
Yiwen Liu, Xiaoxiao Sun, Wenxuan Zhong +1
Very often for the same scientific question, there may exist different techniques or experiments that measure the same numerical quantity. Historically, various methods have been d…