504 citations · 2k across the 109 of their papers we have counts for
5 papers · 2 filters
The Chi-Square Test of Distance Correlation
Cencheng Shen, Sambit Panda, Joshua T. Vogelstein
Distance correlation has gained much recent attention in the data science community: the sample statistic is straightforward to compute and asymptotically equals zero if and only i…
Universally Consistent K-Sample Tests via Dependence Measures
Sambit Panda, Cencheng Shen, Ronan Perry +4
The K-sample testing problem involves determining whether K groups of data points are each drawn from the same distribution. Analysis of variance is arguably the most classical met…
Independence Testing for Temporal Data
Cencheng Shen, Jaewon Chung, Ronak Mehta +2
Temporal data are increasingly prevalent in modern data science. A fundamental question is whether two time series are related or not. Existing approaches often have limitations, s…
Geodesic Learning via Unsupervised Decision Forests
Meghana Madhyastha, Percy Li, James Browne +4
Geodesic distance is the shortest path between two points in a Riemannian manifold. Manifold learning algorithms, such as Isomap, seek to learn a manifold that preserves geodesic d…
Vertex Classification on Weighted Networks
Hayden Helm, Joshua Vogelstein, Carey Priebe
This paper proposes a discrimination technique for vertices in a weighted network. We assume that the edge weights and adjacencies in the network are conditionally independent and…