Comment author: patrickmclaren 24 May 2014 12:42:42AM *  9 points [-]

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.

Comment author: ScottMessick 12 July 2012 06:54:23PM *  16 points [-]

I had long ago (but after being heavily influenced by Overcoming Bias) thought that signaling could be seen simply as a corollary to Bayes' theorem. That is, when one says something, one knows that its effect on a listener will depend on the listener's rational updating on the fact that one said it. If one wants the listener to behave as if X is true, one should say something that the listener would only expect in case X is true.

Thinking in this way, one quickly arrives at conclusions like "oh, so hard-to-fake signals are stronger" and "if everyone starts sending the same signal in the same way, that makes it a lot weaker", which test quite well against observations of the real world.

Powerful corollary: we should expect signaling, along with these basic properties, to be prominent in any group of intelligent minds. For example, math departments and alien civilizations. (Non-example: solitary AI foom.)

Comment author: patrickmclaren 23 May 2014 02:25:07PM *  3 points [-]

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.

Comment author: lukeprog 30 October 2013 08:59:22PM 4 points [-]

Berger is highly technical, not much of an introduction.

On Bayesian statistics, Bayesian Data Analaysis is a classic.

"Bayesian decision theory" usually just means "normal decision theory," so you could start with my FAQ. Though when decision theory is taught from a statistics book rather than an economic book, they use slightly different terminology, e.g. they set things up with a loss function rather than a utility function. For an intro to decision theory from the Bayesian statistics angle, Introduction to Statistical Decision Theory is pretty thorough, and more accessible than Berger.

Comment author: patrickmclaren 30 October 2013 10:35:02PM 0 points [-]

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.

Comment author: patrickmclaren 30 October 2013 01:42:22PM 0 points [-]

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.

Comment author: patrickmclaren 06 October 2013 03:46:36PM 4 points [-]

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.

Comment author: Manfred 29 August 2013 04:15:12PM 1 point [-]

Could you explain?

Comment author: patrickmclaren 29 August 2013 08:45:36PM *  0 points [-]

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:

possible_properties.=.[]
for.p.in.Object.properties():
....for.x.in.training_set:
........if.not.x.has_property(p):
............break
....possible_properties.append(p)

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

irrelevant_properties.=.[]
for.x.in.negative_set:
....for.property.in.x.properties():
........irrelevant_properties.append(property)
relevant_properties.=.[]
for.p.in.Object.properties():
....for.x.in.positive_set:
.......if.not.x.has_property(p).or.p.in.irrelevant_properties:
............break
....relevant_properties.append(p)

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.

Comment author: niceguyanon 27 August 2013 05:26:00AM 4 points [-]

Any tips on journal keeping, specifically the format or style of writing?

I've been keeping a journal but I am unsatisfied with the result. I have no methodology, some days I write as if speaking to a future me, some I write as if to an audience, and some days I write essays, and others I just list what I have done. As a result, my journal is difficult to read, it doesn't have a consistent feel.

Comment author: patrickmclaren 29 August 2013 04:09:44PM 0 points [-]

I write paragraphs beneath headings, to prevent rambling.

Comment author: Lumifer 28 August 2013 08:30:10PM 4 points [-]

Keep in mind that the definition of a sociopath is more or less "one who treats other people as low-level NPCs".

Comment author: patrickmclaren 29 August 2013 04:07:15PM *  2 points [-]

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

Comment author: patrickmclaren 29 August 2013 03:55:26PM 1 point [-]

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

Comment author: patrickmclaren 29 August 2013 03:34:28PM *  1 point [-]

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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