Upcoming

So without further ado, here are the posts I plan to make:

  1. Exotic python data structures and where to find them (heapq, OrderedDict, Deque, bisect)
  2. Onsite interview with Microsoft
  3. Reparameterization tricks: Gaussian vs gumbel
  4. The REINFORCE gradient estimator
  5. Probability notations
  6. Research itinerary
  7. Birthday post
  8. ABD, L1, and Deep learning Symposium follow-up
  9. Scale AI follow-up
  10. The supremum IS big-O notation (usually we want the TIGHTEST worst case bound)
  11. Model vs Data Parallelism
  12. [Some more reinforcement learning][1]
  13. [Some more reinforcement learning]1

(Note that the markdown in preview does not exactly work with some more exotic features, like citations and references)

See you soon!

Nice link aggregation:

  1. http://www.cs.toronto.edu/~zemel/documents/411/rltutorial.pdf [return]
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