AggressivequestionThere is a slidewhere youunderstandabsolutelynothing“Is thatboundtight?”MangaindexInversepropensityscoring/weightingGraphdown andto therightIntimidatingequationRewardmodelGraph upand tothe rightNetflixPlot comparingperformance oftheir algorithm toanotheralgorithmQuadrantdiagramRegretboundInverseReinforcementlearningAV/Zoomissues“Dataefficiency”“The answerto thatquestion ison the nextslide”Someone isat least 5-10minutes lateYahoodatasetDirectmethodOptimizationproblem 2Bandits withcostlyrewardobservationsA committeemember islate to the AexamOptimizationproblem 1MVALSpotifyReinforcementlearningAggressivequestionThere is a slidewhere youunderstandabsolutelynothing“Is thatboundtight?”MangaindexInversepropensityscoring/weightingGraphdown andto therightIntimidatingequationRewardmodelGraph upand tothe rightNetflixPlot comparingperformance oftheir algorithm toanotheralgorithmQuadrantdiagramRegretboundInverseReinforcementlearningAV/Zoomissues“Dataefficiency”“The answerto thatquestion ison the nextslide”Someone isat least 5-10minutes lateYahoodatasetDirectmethodOptimizationproblem 2Bandits withcostlyrewardobservationsA committeemember islate to the AexamOptimizationproblem 1MVALSpotifyReinforcementlearning

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.


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