MangaindexOptimizationproblem 1Graph upand tothe right“Is thatboundtight?”AggressivequestionPlot comparingperformance oftheir algorithm toanotheralgorithmInversepropensityscoring/weightingSpotifyNetflixYahoodataset“The answerto thatquestion ison the nextslide”Optimizationproblem 2“Dataefficiency”RegretboundThere is a slidewhere youunderstandabsolutelynothingMVALBandits withcostlyrewardobservationsInverseReinforcementlearningGraphdown andto therightAV/ZoomissuesQuadrantdiagramSomeone isat least 5-10minutes lateRewardmodelReinforcementlearningA committeemember islate to the AexamIntimidatingequationDirectmethodMangaindexOptimizationproblem 1Graph upand tothe right“Is thatboundtight?”AggressivequestionPlot comparingperformance oftheir algorithm toanotheralgorithmInversepropensityscoring/weightingSpotifyNetflixYahoodataset“The answerto thatquestion ison the nextslide”Optimizationproblem 2“Dataefficiency”RegretboundThere is a slidewhere youunderstandabsolutelynothingMVALBandits withcostlyrewardobservationsInverseReinforcementlearningGraphdown andto therightAV/ZoomissuesQuadrantdiagramSomeone isat least 5-10minutes lateRewardmodelReinforcementlearningA committeemember islate to the AexamIntimidatingequationDirectmethod

Aaron's A exam - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Manga index
  2. Optimization problem 1
  3. Graph up and to the right
  4. “Is that bound tight?”
  5. Aggressive question
  6. Plot comparing performance of their algorithm to another algorithm
  7. Inverse propensity scoring/weighting
  8. Spotify
  9. Netflix
  10. Yahoo dataset
  11. “The answer to that question is on the next slide”
  12. Optimization problem 2
  13. “Data efficiency”
  14. Regret bound
  15. There is a slide where you understand absolutely nothing
  16. MVAL
  17. Bandits with costly reward observations
  18. Inverse Reinforcement learning
  19. Graph down and to the right
  20. AV/Zoom issues
  21. Quadrant diagram
  22. Someone is at least 5-10 minutes late
  23. Reward model
  24. Reinforcement learning
  25. A committee member is late to the A exam
  26. Intimidating equation
  27. Direct method