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I've been searching LessWrong for prior discussions on Anxiety and I'm not getting very many hits. This surprised me. Obviously there have been well developed discussions on arkrasia, and ugh fields, yet little regarding their evil siblings Anxiety, Panic, and Mania.

I'd be interested to hear what people have to say about these topics from a rationalist's perspective. I wonder if anyone has developed any tricks, to calm the storm, and search for a third alternative.

Of course, first, and foremost, in such situations one should seek medical advice.

EDIT: Some very slightly related discussions: Don't Fear Failure, Hoping to start a discussion about overcoming insecurity.

Your math department example reminds me of a few experiences. From time to time, I'd be present when a small group of 3-4 professors were quietly discussing roadblocks in their research. Problems would be introduced, mentioning a number of unexpectedly connected fields, Symplectic This-Thats, and the Cohomology of Riff-Raffs. Eventually as the speaker relaxed and their anxiety settled, it would turn out that they were having trouble with an inequality and lost a constant along the way. So, the group would get to work, perhaps they would be able to fix the issue, then the next speaker in the circle would start to announce his problem.

What was surprising to me, was that they were not strangers. Most had been friends for over a decade. I wonder if the others were even still listening to the name-dropping. The context it provided wasn't at all helpful for finding a typo, that's for sure. I suppose it may be nice for "Keeping up with the Joneses", so to speak.

Great, thank you very much for the references. I am now reading your FAQ before moving onto the texts, I'll post any comments I have there.

Could anyone provide me with some rigorous mathematical references on Statistical Hypotheses Testing, and Bayesian Decision Theory? I am not an expert in this area, and am not aware of the standard texts. So far I have found

  • Statistical Decision Theory and Bayesian Analysis - Berger
  • Bayesian and Frequentist Regression Methods - Wakefield

Currently, I am leaning towards purchasing Berger's book. I am looking for texts similar in style and content to those of Springer's GTM series. It looks like the Springer Series in Statistics may be sufficient.

Started an additional job where I wrote some voice recognition software to automate video lecture transcription with a fairly high success rate (82.13%). I also streamlined the training process for non-technical people.

Hopefully, if there's a thread next month, I'll be posting about the GRE subject test in Mathematics.

Sure, will you take some python code as an example? I had to replace spaces with periods, the verbatim formatting doesn't seem to take into account python indented by 4 spaces.

Without taking into negative training data into account:


Taking negative training data into account, here we have a 'positive set', and a 'negative set':



See the difference? In the second case, 'potential properties' is smaller. Note that this is not an optimal solution, since it looks up all possible properties in order to find the common properties of a training set, I wrote it because it's a little more succinct than intersections.

I write paragraphs beneath headings, to prevent rambling.

Indeed, and people would do well to remember that there may be situations wherein you are in fact the relatively "low-level NPC".

Recognizing some common characteristics of objects to be placed in the not 'odd' bin would also lower the upper bound on the complexity.

Just did this last night, actually. I've been noticing that my major goals, i.e. both professional and research goals have been playing host to a number of other side projects, like: learn this new language, write this cool script, start learning the latest trendy math field.

What I ended up doing is allocating 6 hours to my side projects on the weekends, promising to myself that I will use time-tracking, and once 6 hours is filled, spread over whichever projects, then I will not spend any more time on them.

Regarding annoyances, I simply wrote down everything that was annoying me, came up with solutions, wrote the solutions (and deadlines) in my planner, and then I was able to cross them off the list. Once I really got going, my days seemed to become a lot simpler, just because I could see has been bothering and distracting me.

Long term goals were still good. I had effectively been suffering feature creep for a while, and for now I can work much more efficiently.

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