AV/ZoomissuesOptimizationproblem 1Inversepropensityscoring/weightingSomeoneis at least5 minuteslateGraphdown andto theright“The answerto thatquestion ison the nextslide”InverseReinforcementlearningThere is a slidewhere youunderstandabsolutelynothingDirectmethodSongsPlot comparingperformance oftheir algorithm toanotheralgorithmOptimizationproblem 2AggressivequestionMVALTargetpolicyRegretbound“Dataefficiency”Killianmakesa jokeYahoodatasetGraph upand tothe rightBandits withcostlyrewardobservationsIntimidatingequationA committeemember islate to the AexamRewardmodelReinforcementlearningQuadrantdiagramBalancedestimatorAV/ZoomissuesOptimizationproblem 1Inversepropensityscoring/weightingSomeoneis at least5 minuteslateGraphdown andto theright“The answerto thatquestion ison the nextslide”InverseReinforcementlearningThere is a slidewhere youunderstandabsolutelynothingDirectmethodSongsPlot comparingperformance oftheir algorithm toanotheralgorithmOptimizationproblem 2AggressivequestionMVALTargetpolicyRegretbound“Dataefficiency”Killianmakesa jokeYahoodatasetGraph upand tothe rightBandits withcostlyrewardobservationsIntimidatingequationA committeemember islate to the AexamRewardmodelReinforcementlearningQuadrantdiagramBalancedestimator

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