Graphdown andto therightOptimizationproblem 1A committeemember islate to the AexamQuadrantdiagramAggressivequestion“Dataefficiency”YahoodatasetMVALPlot comparingperformance oftheir algorithm toanotheralgorithmOptimizationproblem 2RegretboundRewardmodelAV/ZoomissuesDirectmethodSomeone isat least 5-10minutes lateIntimidatingequationReinforcementlearningBandits withcostlyrewardobservationsMangaindexSpotifyInverseReinforcementlearningThere is a slidewhere youunderstandabsolutelynothing“Is thatboundtight?”“The answerto thatquestion ison the nextslide”Graph upand tothe rightInversepropensityscoring/weightingNetflixGraphdown andto therightOptimizationproblem 1A committeemember islate to the AexamQuadrantdiagramAggressivequestion“Dataefficiency”YahoodatasetMVALPlot comparingperformance oftheir algorithm toanotheralgorithmOptimizationproblem 2RegretboundRewardmodelAV/ZoomissuesDirectmethodSomeone isat least 5-10minutes lateIntimidatingequationReinforcementlearningBandits withcostlyrewardobservationsMangaindexSpotifyInverseReinforcementlearningThere is a slidewhere youunderstandabsolutelynothing“Is thatboundtight?”“The answerto thatquestion ison the nextslide”Graph upand tothe rightInversepropensityscoring/weightingNetflix

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