Name
Abstract | ||
|---|---|---|
A fundamental task in AI is to assess (in)dependence between mixed-type variables (text, image, sound). We propose a Bayesian kernelised correlation test of (in)dependence using a Dirichlet process model. The new measure of (in)dependence allows us to answer some fundamental questions: Based on data, are (mixed-type) variables independent? How likely is dependence/independence to hold? How high is... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/DSAA53316.2021.9564124 | 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA) |
Keywords | DocType | ISBN |
Mixed-type data,Independence test,Bayesian,Kernelised test | Conference | 978-1-6654-2099-0 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessio Benavoli | 1 | 229 | 30.52 |
| Cassio de Campos | 2 | 0 | 0.34 |