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Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems - Foundations and Trends (R) in Machine Learning Sebastien Bubeck
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Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems - Foundations and Trends (R) in Machine Learning
Sebastien Bubeck
Mathematically, a multi-armed bandit is defined by the payoff process associated with each option. In this book, the focus is on two extreme cases in which the analysis of regret is particularly simple and elegant: independent and identically distributed payoffs and adversarial payoffs.
138 pages
| Mediji | Grāmatas Paperback Book (Grāmata ar mīksto vāku un līmēto muguru) |
| Izlaists | 2012. gada 12. decembris |
| ISBN13 | 9781601986269 |
| Izdevēji | now publishers Inc |
| Lapas | 138 |
| Izmēri | 234 × 159 × 8 mm · 204 g |
| Valoda | Angļu |
