
Great Ideas in Theoretical Computer Science - tu7001
http://www.cs.cmu.edu/~aada/courses/15251f15/www/schedule.html
======
z1mm32m4n
Some context for those who don't go/didn't go CMU:

15-251 Great Theoretical Ideas in CS is the freshman spring semester discrete
math & theoretical CS (a follow up to the discrete math course they take
freshman fall). The course itself goes for breadth over depth. In this aspect,
it serves as a solid foundation for all theory classes students take going
forward. It's a class where students learn proof techniques, collaboration,
and problem solving.

The course is often praised for its rigor. The problem sets require a fair
amount of work to complete, and the course staff sets a high standard for
responses.

On the other hand, it commonly receives criticism for being quite intense as a
freshman class. Many CMU students look back on it as one of the hardest
classes they took.

I personally feel quite lucky to have taken 251. It gave me a foundation to
appreciate a lot of deeper CS topics, and taking it freshman year meant I had
3 years more to put it to use.

~~~
kutkloon7
I was just about to comment that the topics seem really intense. I got the
impression that Carnegie Mellon is an excellent university with very high
standards (much better than Harvard, Stanford, Berkeley, etc., which are
prestigious and have lots of professors which do great research, but the
actual scientific education is good, but not extraordinary, and moreover, the
courses are not very hard from what I've heard).

It happened multiple times that I googled some relatively obscure topic, and I
found multiple excellent sources from Carnegie Mellon professors. For example,
there is this excellent document [1] by Jonathan Shewchuk, about the conjugate
gradient method, and you will found as many as four lectures about DRAM memory
on youtube.

[1] [https://www.cs.cmu.edu/~quake-papers/painless-conjugate-
grad...](https://www.cs.cmu.edu/~quake-papers/painless-conjugate-gradient.pdf)

~~~
laughinghan
My friends had him and I hear Jonathan Shewchuck is indeed an excellent
teacher. However, he has never been a CMU professor. In 1994, when your link
was dated, he was getting his PhD at CMU, and since 1998 he's been a professor
at UC Berkeley (where I went):
[https://people.eecs.berkeley.edu/~jrs/](https://people.eecs.berkeley.edu/~jrs/)

I have no doubts about CMU's excellence, but I found Berkeley's undergrad CS
education to be quite good. There certainly were research professors who were
bad teachers, but many like Shewchuck were outstanding teachers, and there
were also several Teaching Professors whose job description to focus is more
on teaching than research, like Dan Garcia, Paul Hilfinger, John DeNero, and
Brian Harvey (since retired):
[https://www2.eecs.berkeley.edu/Faculty/Lists/faculty.html](https://www2.eecs.berkeley.edu/Faculty/Lists/faculty.html)

I too have heard that private schools like Harvard and Stanford are not very
hard once you get in, just very hard to get into (though I can't speak from
experience). I haven't heard people say that about Berkeley, which is a public
school so it doesn't have shareholders where alumni can form a controlling
majority, and it's funded more by the state than by tuition. That also
certainly was not the experience of myself or anyone I know.

~~~
cbHXBY1D
I also studied EECS at Berkeley and had Shewchuck.

There's this mentality at Berkeley that the EECS classes are the hardest and
most competitive in the country (and that private schools just give everyone
A's) but after meeting many CMU graduates I realized that it's program is also
similarly rigorous. The classes might not be as _competitive_ but then again I
don't think that means it's worse for it.

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rawnlq
Recording of the lectures for Spring 2016:
[https://www.youtube.com/watch?list=PLm3J0oaFux3aafQm568blS9b...](https://www.youtube.com/watch?list=PLm3J0oaFux3aafQm568blS9blxtA_EWQv&v=uaAvVNWvi4A)

Slides:
[http://www.cs.cmu.edu/~aada/courses/15251s16/www/schedule.ht...](http://www.cs.cmu.edu/~aada/courses/15251s16/www/schedule.html)

~~~
tu7001
Those YouTube lectures are prof O'Donnell course. I don't know if they match.

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Chathamization
I wonder what kind of retention there is. Is one day of class studying quantum
computation going to be particularly useful to people when they study it 6
months or 2 years later?

I've lately studied a bit of program design when it comes to working out. A
lot of effort goes into designing workout programs, making the programs
efficient, trying to get the maximum results from the least amount of effort.
There's a clear progression and a clear way of measuring progress. Every
exercise, stretch, and movement is supposed to a particular function that best
moves you toward your goal. Particular muscle sets are targeted at particular
intensities for particular intervals on particular days. There's a reason for
every specific decision that gets made.

You can contrast this with the aimless way a lot of people workout. They go to
the gym, they do whatever exercises or work on whatever machines seem like a
good idea to them at the moment, and hope it increases their fitness in some
non-specific way. Lacking good metrics for measuring effectiveness, they often
judge a workout by how sore it makes them the next day (an extremely poor way
to measure effectiveness). It's not that this approach can't improve your
health, it's just that it's extremely inefficient compared to the more goal
orientated and progression based system.

In my experience most universities follow the aimless second approach -
throwing what they can at the students, hoping some of it sticks, and judging
the courses based on difficulty (this usually becomes even more obvious when
professors explain their courses). I don't think I've come across any study
measuring the effectiveness and metrics of different programs and progression
paths.

~~~
bichiliad
It's a bit more than it seems, on the surface. You're not just expected to
pick up what the professors lecture about, but to take it and apply it to a
sampling of fairly advanced problems. You end up doing a lot of learning on
your own (or in a small group) while completing the homework.

To use your gym analogy, it's like focusing on one muscle group per week. On
Monday, you're shown proper form and technique for a squat, but by the
following Monday, you'd better be able to squat significantly more than you
could a week ago (and you'll get graded on it). Are you going to become a
competitive squat weight lifter? Absolutely not. Do you now know proper form,
and understand what it takes to train properly? Almost certainly.

I'd also note two things:

\- Most topics covered were useful in later courses.

\- A lot of the credit for this course's success can be given as much to
really, really dedicated TAs as it can to the professors.

 _(Note: I took this course my freshman year, it was blisteringly hard, and I
wouldn 't have traded anything for it.)_

------
westurner
List of important publications in computer science
[https://en.wikipedia.org/wiki/List_of_important_publications...](https://en.wikipedia.org/wiki/List_of_important_publications_in_computer_science)

[http://paperswelove.org/](http://paperswelove.org/)

[https://github.com/papers-we-love/papers-we-love#other-
good-...](https://github.com/papers-we-love/papers-we-love#other-good-places-
to-find-papers)

------
sidusknight
Most of the links are behind a login. Why even post this here?

~~~
kutkloon7
The slides are not, and there are so many links that are directly behind a
paywall on hacker news... Those really bother me.

~~~
dmix
WSJ style paywall articles are bypassable via the 'web' link. Not quite the
same at all.

~~~
kuschku
If you are in the US, that is. Their paywall bypass doesn’t work for all
countries.

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75dvtwin
reading one of the PDFs referenced
[http://www.cs.cmu.edu/~aada/courses/15251f15/www/slides/lec0...](http://www.cs.cmu.edu/~aada/courses/15251f15/www/slides/lec05.pdf)

Why other mathematicians at the time, were so nasty towards Cantor's ideas?
The quotes noted in the PDF -- just sound nasty and dismissive (or may be this
is not the whole story)

~~~
addicted
You are highly underestimating the mental leaps required to understand
infinity pre Cantor. It's not surprising at all that people should find it
ridiculous and get especially angry about it because they couldn't really
explain why it was wrong, despite it just seeming like complete BS to them.

It's like telling a lay person (or even many mathematics students for that
matter) that 0.999999.... = 1. They understand the proofs, but it's so against
their intuition there is a visceral negative reaction to it.

~~~
pacala
There is no such thing as 0.9... There is 0.9[k], for k as large as you'd
like. However, no matter which k you pick, I can squirrel a number between
0.9[k] and 1, for example 0.9[k]5. Your alleged proof is wrong :p

~~~
cgmg
> There is no such thing as 0.9...

Yes, there is. Ask yourself: What's the decimal expansion of 1/3, or pi?

~~~
wyldfire
I'm not a math pro but I don't think those are good evidence to refute that
claim. I have no idea whether the claim is valid or not, though I vaguely
recall this discussion from school.

From your examples -- one's a ratio and the other is irrational. Almost as if
you suggest "The set of real numbers exists, ergo 0.999999... exists"?

~~~
yorwba
The battle over the question whether or not something exists in the
mathematical sense has essentially been won by the formalists, who will allow
any definition to claim the existence of something so long as it is consistent
with the rest of mathematics.

Then, given that 0.99999... exists, what useful properties could it possibly
have, if it is to be treated as a number.

0.99999... = 0.9999... * 1 = 0.99999... * 9/9 = 0.99999... * (10 - 1)/9 =
(0.99999... * 10 - 0.99999... * 1)/9 = (9.99999... - 0.99999...)/9 =
9.00000.../9 = 9/9 = 1

So _if_ 0.99999... exists and has the same arithmetic properties as decimal
expansions of rational numbers, its value _must_ be 1. Now whether you think
it should have these properties is an entirely different question, but most
mathematicians seem to like it this way.

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anaccountwow
Why such an old version ;-;

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dnautics
no love for coding theory!

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raister
The Markov Chains lecture has a huge 'meh!' feeling attached to it, I'd be
better of not clicking on that PDF in the first place.

