AV/ZoomissuesIntimidatingequationQuadrantdiagramSomeoneis at least5 minuteslateBandits withcostlyrewardobservationsKillianmakesa jokeReinforcementlearningDirectmethod“The answerto thatquestion ison the nextslide”“Dataefficiency”Graph upand tothe rightA committeemember islate to the AexamMVALThere is a slidewhere youunderstandabsolutelynothingInverseReinforcementlearningSongsAggressivequestionRewardmodelPlot comparingperformance oftheir algorithm toanotheralgorithmBalancedestimatorOptimizationproblem 1Inversepropensityscoring/weightingRegretboundGraphdown andto therightTargetpolicyOptimizationproblem 2YahoodatasetAV/ZoomissuesIntimidatingequationQuadrantdiagramSomeoneis at least5 minuteslateBandits withcostlyrewardobservationsKillianmakesa jokeReinforcementlearningDirectmethod“The answerto thatquestion ison the nextslide”“Dataefficiency”Graph upand tothe rightA committeemember islate to the AexamMVALThere is a slidewhere youunderstandabsolutelynothingInverseReinforcementlearningSongsAggressivequestionRewardmodelPlot comparingperformance oftheir algorithm toanotheralgorithmBalancedestimatorOptimizationproblem 1Inversepropensityscoring/weightingRegretboundGraphdown andto therightTargetpolicyOptimizationproblem 2Yahoodataset

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