Optimizationproblem 2InverseReinforcementlearningGraphdown andto therightOptimizationproblem 1AggressivequestionIntimidatingequation“Is thatboundtight?”RegretboundInversepropensityscoring/weightingReinforcementlearningSomeone isat least 5-10minutes lateQuadrantdiagramMVALPlot comparingperformance oftheir algorithm toanotheralgorithmGraph upand tothe rightA committeemember islate to the AexamRewardmodelBandits withcostlyrewardobservationsDirectmethodYahoodatasetThere is a slidewhere youunderstandabsolutelynothing“Dataefficiency”NetflixMangaindex“The answerto thatquestion ison the nextslide”SpotifyAV/ZoomissuesOptimizationproblem 2InverseReinforcementlearningGraphdown andto therightOptimizationproblem 1AggressivequestionIntimidatingequation“Is thatboundtight?”RegretboundInversepropensityscoring/weightingReinforcementlearningSomeone isat least 5-10minutes lateQuadrantdiagramMVALPlot comparingperformance oftheir algorithm toanotheralgorithmGraph upand tothe rightA committeemember islate to the AexamRewardmodelBandits withcostlyrewardobservationsDirectmethodYahoodatasetThere is a slidewhere youunderstandabsolutelynothing“Dataefficiency”NetflixMangaindex“The answerto thatquestion ison the nextslide”SpotifyAV/Zoomissues

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