Search Results for author: Sambit Panda

Found 6 papers, 4 papers with code

Simplest Streaming Trees

2 code implementations16 Oct 2021 Haoyin Xu, Jayanta Dey, Sambit Panda, Joshua T. Vogelstein

Nonetheless, we found that those state-of-the-art algorithms suffer from a number of drawbacks, including performing very poorly on some problems and requiring a huge amount of memory on others.

Continual Learning Transfer Learning

The Chi-Square Test of Distance Correlation

1 code implementation27 Dec 2019 Cencheng Shen, Sambit Panda, Joshua T. Vogelstein

One major bottleneck is the testing process: because the null distribution of distance correlation depends on the underlying random variables and metric choice, it typically requires a permutation test to estimate the null and compute the p-value, which is very costly for large amount of data.

Nonpar MANOVA via Independence Testing

no code implementations20 Oct 2019 Sambit Panda, Cencheng Shen, Ronan Perry, Jelle Zorn, Antoine Lutz, Carey E. Priebe, Joshua T. Vogelstein

The $k$-sample testing problem tests whether or not $k$ groups of data points are sampled from the same distribution.

Two-sample testing

hyppo: A Multivariate Hypothesis Testing Python Package

4 code implementations3 Jul 2019 Sambit Panda, Satish Palaniappan, Junhao Xiong, Eric W. Bridgeford, Ronak Mehta, Cencheng Shen, Joshua T. Vogelstein

We introduce hyppo, a unified library for performing multivariate hypothesis testing, including independence, two-sample, and k-sample testing.

Two-sample testing

Learning Interpretable Characteristic Kernels via Decision Forests

no code implementations30 Nov 2018 Cencheng Shen, Sambit Panda, Joshua T. Vogelstein

It has been demonstrated that these proximity matrices can be thought of as kernels, connecting the decision forest literature to the extensive kernel machine literature.

Feature Importance General Classification

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