MVALOptimizationproblem 1ReinforcementlearningDirectmethodSpotifyGraphdown andto therightInversepropensityscoring/weightingPlot comparingperformance oftheir algorithm toanotheralgorithmSomeone isat least 5-10minutes lateIntimidatingequationMangaindexNetflixAggressivequestionYahoodatasetBandits withcostlyrewardobservationsGraph upand tothe rightA committeemember islate to the AexamInverseReinforcementlearningAV/Zoomissues“The answerto thatquestion ison the nextslide”QuadrantdiagramRegretbound“Is thatboundtight?”“Dataefficiency”There is a slidewhere youunderstandabsolutelynothingOptimizationproblem 2RewardmodelMVALOptimizationproblem 1ReinforcementlearningDirectmethodSpotifyGraphdown andto therightInversepropensityscoring/weightingPlot comparingperformance oftheir algorithm toanotheralgorithmSomeone isat least 5-10minutes lateIntimidatingequationMangaindexNetflixAggressivequestionYahoodatasetBandits withcostlyrewardobservationsGraph upand tothe rightA committeemember islate to the AexamInverseReinforcementlearningAV/Zoomissues“The answerto thatquestion ison the nextslide”QuadrantdiagramRegretbound“Is thatboundtight?”“Dataefficiency”There is a slidewhere youunderstandabsolutelynothingOptimizationproblem 2Rewardmodel

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