Graphdown andto therightReinforcementlearningThere is a slidewhere youunderstandabsolutelynothingRegretboundDirectmethod“Is thatboundtight?”Plot comparingperformance oftheir algorithm toanotheralgorithmInverseReinforcementlearningGraph upand tothe right“Dataefficiency”Bandits withcostlyrewardobservationsRewardmodelAV/ZoomissuesQuadrantdiagramMVALInversepropensityscoring/weightingSomeone isat least 5-10minutes lateA committeemember islate to the AexamNetflixOptimizationproblem 1YahoodatasetSpotifyOptimizationproblem 2“The answerto thatquestion ison the nextslide”IntimidatingequationMangaindexAggressivequestionGraphdown andto therightReinforcementlearningThere is a slidewhere youunderstandabsolutelynothingRegretboundDirectmethod“Is thatboundtight?”Plot comparingperformance oftheir algorithm toanotheralgorithmInverseReinforcementlearningGraph upand tothe right“Dataefficiency”Bandits withcostlyrewardobservationsRewardmodelAV/ZoomissuesQuadrantdiagramMVALInversepropensityscoring/weightingSomeone isat least 5-10minutes lateA committeemember islate to the AexamNetflixOptimizationproblem 1YahoodatasetSpotifyOptimizationproblem 2“The answerto thatquestion ison the nextslide”IntimidatingequationMangaindexAggressivequestion

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