IntimidatingequationMVALYahoodatasetInversepropensityscoring/weighting“The answerto thatquestion ison the nextslide”RewardmodelSomeoneis at least5 minuteslateKillianmakesa jokeOptimizationproblem 1Bandits withcostlyrewardobservationsInverseReinforcementlearningAV/ZoomissuesSongsReinforcementlearningRegretboundQuadrantdiagramOptimizationproblem 2A committeemember islate to the AexamPlot comparingperformance oftheir algorithm toanotheralgorithm“Dataefficiency”Graph upand tothe rightThere is a slidewhere youunderstandabsolutelynothingDirectmethodBalancedestimatorTargetpolicyGraphdown andto therightAggressivequestionIntimidatingequationMVALYahoodatasetInversepropensityscoring/weighting“The answerto thatquestion ison the nextslide”RewardmodelSomeoneis at least5 minuteslateKillianmakesa jokeOptimizationproblem 1Bandits withcostlyrewardobservationsInverseReinforcementlearningAV/ZoomissuesSongsReinforcementlearningRegretboundQuadrantdiagramOptimizationproblem 2A committeemember islate to the AexamPlot comparingperformance oftheir algorithm toanotheralgorithm“Dataefficiency”Graph upand tothe rightThere is a slidewhere youunderstandabsolutelynothingDirectmethodBalancedestimatorTargetpolicyGraphdown andto therightAggressivequestion

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