How to beat the Casino and know when your Code has converged : Mixing Times of Markov Chains
| Wed May 6, 14:30-15:00 (2 weeks from now) | |
| Lecture held in MVL14. |
Abstract: I invite you to read the category that fits you best.
You are a statistician : You deal with scarry distributions which you sample using MCMCs. But how do you know when your algorithm has actually converged ?
You are a probabilist : The ergodic theorem tells you kindly that your favorite Markov chain converges to stationarity...eventually. But it stays silent about when that happens.
You are about to bet your mortgage in Las Vegas: Is the deck of cards the croupier is shuffling really that random; or is there an opportunity to mathematically beat the casino ?
If at least one of these questions raises your interest, you're välkommen to hear more about mixing times! :)
Mathematics
Audience: general audience
Series comments: Rooms and times may vary, please check the latest update. In-person only.
| Organizers: | Anna Theorin Johansson*, Lotta Eriksson* |
| *contact for this listing |