InverseReinforcementlearning“The answerto thatquestion ison the nextslide”AggressivequestionAV/ZoomissuesTargetpolicyGraphdown andto therightGraph upand tothe rightKillianmakesa jokeMVALBalancedestimatorSongsBandits withcostlyrewardobservationsThere is a slidewhere youunderstandabsolutelynothingA committeemember islate to the Aexam“Dataefficiency”IntimidatingequationInversepropensityscoring/weightingOptimizationproblem 1Someoneis at least5 minuteslatePlot comparingperformance oftheir algorithm toanotheralgorithmReinforcementlearningRewardmodelYahoodatasetOptimizationproblem 2DirectmethodRegretboundQuadrantdiagramInverseReinforcementlearning“The answerto thatquestion ison the nextslide”AggressivequestionAV/ZoomissuesTargetpolicyGraphdown andto therightGraph upand tothe rightKillianmakesa jokeMVALBalancedestimatorSongsBandits withcostlyrewardobservationsThere is a slidewhere youunderstandabsolutelynothingA committeemember islate to the Aexam“Dataefficiency”IntimidatingequationInversepropensityscoring/weightingOptimizationproblem 1Someoneis at least5 minuteslatePlot comparingperformance oftheir algorithm toanotheralgorithmReinforcementlearningRewardmodelYahoodatasetOptimizationproblem 2DirectmethodRegretboundQuadrantdiagram

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