89 citations · 430 across the 37 of their papers we have counts for
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Learning Interpretable Characteristic Kernels via Decision Forests
Sambit Panda, Cencheng Shen, Joshua T. Vogelstein
Decision forests are widely used for classification and regression tasks. A lesser known property of tree-based methods is that one can construct a proximity matrix from the tree(s…
The Exact Equivalence of Distance and Kernel Methods for Hypothesis Testing
Cencheng Shen, Joshua T. Vogelstein
Distance-based tests, also called "energy statistics", are leading methods for two-sample and independence tests from the statistics community. Kernel-based tests, developed from "…
Discovering the Signal Subgraph: An Iterative Screening Approach on Graphs
Cencheng Shen, Shangsi Wang, Alexandra Badea +2
Supervised learning on graphs is a challenging task due to the high dimensionality and inherent structural dependencies in the data, where each edge depends on a pair of vertices.…