React Roadmap for Beginners in 2022.

🧵

Andy McCabe has some explaining to do.

Andrew McCabe was reported to the FBI’s Office of Public Affairs for making an unauthorized leak of classified info to the media about @GenFlynn in early February 2017.

If you’ve wondered exactly who it was who leaked the classified info from that intelligence report on @GenFlynn’s phone calls with then-Russian ambassador Kislyak to the media, you are right now seeing a huge honking clue who it was.

To those responding to this info by sneering "Nothing's gonna happen":

Up.

Your.

Game.

You just might be too stupid to be following me.

The then-Deputy Director of the FBI get's caught targeting @GenFlynn with an illegal leak so he can 'investigated' by Peter Strzok?

Now that we know it was McCabe who set up Flynn for a fake 'perjury' investigation by his pet attack dog, Peter Strzok, the next name that's going to surface is...Joseph Pientka.

The Straddle is my favorite trade these days. But more often than not, one needs to adjust to make a good return from it. There are many ways to do this depending on your view, psychology and imagination. Will discuss a few that I use

The Straddle is a delta neutral strategy and it is important to keep deltas in check during the course of the Trade and not let them run away from you. Of course Volatility is the elephant in the room- but not going there as that will require a separate discussion

The first and most common method is to go 'inverted.' That is to say to shift the untested side to generate additional Premium and increase the runway to Breakeven. So if you start with a Straddle at 700 and price goes to 740, you can move the PE up to say 720.

How much should you move the untested side? While again this is a matter of skill, experience and artistry, the rule of thumb is to cut deltas by half. Remember, prices will move and you have to allow sufficient room for them to fluctuate

The second method is to shift the entire Straddle in the direction of the move. So if you have a 700 Straddle and Price goes to 740, you can shift the Straddle to 720. If you time this right, it can generally be done at virtually no cost or minimal cost.

Important paper from Google on large batch optimization. They do impressively careful experiments measuring # iterations needed to achieve target validation error at various batch sizes. The main "surprise" is the lack of surprises. [thread]

https://t.co/7QIx5CFdfJ

The paper is a good example of lots of elements of good experimental design. They validate their metric by showing lots of variants give consistent results. They tune hyperparamters separately for each condition, check that optimum isn't at the endpoints, and measure sensitivity.

They have separate experiments where the hold fixed # iterations and # epochs, which (as they explain) measure very different things. They avoid confounds, such as batch norm's artificial dependence between batch size and regularization strength.

When the experiments are done carefully enough, the results are remarkably consistent between different datasets and architectures. Qualitatively, MNIST behaves just like ImageNet.

Importantly, they don't find any evidence for a "sharp/flat optima" effect whereby better optimization leads to worse final results. They have a good discussion of experimental artifacts/confounds in past papers where such effects were reported.