Optimizationproblem 1YahoodatasetThere is a slidewhere youunderstandabsolutelynothing“Is thatboundtight?”NetflixAV/ZoomissuesBandits withcostlyrewardobservationsAggressivequestionReinforcementlearningPlot comparingperformance oftheir algorithm toanotheralgorithmRegretboundOptimizationproblem 2Graph upand tothe rightGraphdown andto therightIntimidatingequationRewardmodelInverseReinforcementlearningDirectmethodA committeemember islate to the AexamSpotifyInversepropensityscoring/weighting“The answerto thatquestion ison the nextslide”MVALSomeone isat least 5-10minutes lateMangaindexQuadrantdiagram“Dataefficiency”Optimizationproblem 1YahoodatasetThere is a slidewhere youunderstandabsolutelynothing“Is thatboundtight?”NetflixAV/ZoomissuesBandits withcostlyrewardobservationsAggressivequestionReinforcementlearningPlot comparingperformance oftheir algorithm toanotheralgorithmRegretboundOptimizationproblem 2Graph upand tothe rightGraphdown andto therightIntimidatingequationRewardmodelInverseReinforcementlearningDirectmethodA committeemember islate to the AexamSpotifyInversepropensityscoring/weighting“The answerto thatquestion ison the nextslide”MVALSomeone isat least 5-10minutes lateMangaindexQuadrantdiagram“Dataefficiency”

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