Timeline for Choosing $k$ different assignments of binary variables in order to capture the largest volume of the joint probability distribution
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Sep 23, 2022 at 7:58 | vote | accept | JanHula | ||
| Sep 18, 2022 at 21:18 | vote | accept | JanHula | ||
| Sep 23, 2022 at 7:58 | |||||
| Sep 18, 2022 at 20:14 | vote | accept | JanHula | ||
| Sep 18, 2022 at 20:14 | |||||
| Sep 18, 2022 at 17:38 | vote | accept | JanHula | ||
| Sep 18, 2022 at 17:39 | |||||
| Sep 18, 2022 at 13:58 | comment | added | RobPratt | Glad to help. Please mark my answer as accepted. Also, ILP solvers have options to stop early based on optimality gap, but I suspect that will not be necessary here. | |
| Sep 18, 2022 at 9:49 | comment | added | JanHula | Thank you. I hoped there would be some way to enumerate the assignments faster if we accept to obtain a suboptimal solution with some approximation guarantee. Maybe I should test the ILP solver to see how fast it is. | |
| Sep 17, 2022 at 15:42 | history | answered | RobPratt | CC BY-SA 4.0 |