Timeline for Distance of distributions of random variables, without PDF
Current License: CC BY-SA 3.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Mar 3, 2017 at 21:19 | comment | added | Henry.L | Yes but you can do it using simple variantional technique, since you have only finite samples this should not cost too much computational time. | |
| Mar 3, 2017 at 21:08 | comment | added | Amir Sagiv | Don't I need to take an infimum over all measures? | |
| Mar 3, 2017 at 20:02 | comment | added | Henry.L | @AmirSagiv I think Wasserstein distance is rather easy to compute since you only have to know $\mu$ and know the moments from $f_i$. I do not think there could be an easier one unless I know what you actually know about $f_i$ further. | |
| Mar 3, 2017 at 9:19 | comment | added | Amir Sagiv | Thanks! It doesn't seem from the paper/the Wiki page that the Wasserstein distance is easily computable. Am I wrong? | |
| S Mar 2, 2017 at 8:21 | history | suggested | Amir Sagiv | CC BY-SA 3.0 |
ADDED links to relevant definitions
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| Mar 2, 2017 at 8:12 | review | Suggested edits | |||
| S Mar 2, 2017 at 8:21 | |||||
| Mar 1, 2017 at 20:13 | history | answered | Henry.L | CC BY-SA 3.0 |