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Algorithms, by Jeff Erickson

jeffe.cs.illinois.edu

111–120 of 245 posts

Re: Algorithms, by Jeff Erickson

#111

Jeff Erickson was my algorithms professor in 2012. He exemplifies the articulate, passionate educator that I wish I had for my other CS subjects. I recognize many of these notes having read them many times in preparation for quite difficult exams - a fun anecdote shared among people who've taken the class is the 25% credit given on any exam question just for writing "I don't know", effectively a reward for acknowledg…

>25% credit given on any exam question just for writing "I don't know", effectively a reward for acknowledging your own shortcoming and for saving the TA the time to decipher a bullshit answer. That’s brilliant, yet I’ve never heard of it. Should be standard scoring for written exams.

This is functionally equivalent to being given negative marks for getting answers wrong, which I've seen on multiple choice tests.

Re: Algorithms, by Jeff Erickson

#112
post #90

Earlier quoted context omitted.

Hi, I'm the author. If you find any particular claim of "obviousness" unclear, submit an issue request! But please don't confuse "straightforward" with "obvious". Sometimes I deliberately gloss over mechanical details because I think they're a distraction from the main point. I'm NOT claiming that you should immediately know how to fill in the details; I'm claiming that filling in the details is boring.

I would agree that words like "obvious" or "trivial" can be disheartening to a learner. If it's obvious to the reader, they know it whether or not you tell them it's obvious. If it's not obvious to them, then they will try to figure it out. Telling this person "it's obvious" only serves to make them feel bad about not getting it right away.

I agree as well. Maybe it serves to alert the reader to when they are missing a piece of prerequisite knowledge, but there are ways to do this that don't create as much friction.

Re: Algorithms, by Jeff Erickson

#114
post #72

Are algorithms useful to learn for a non-programmer? Is there a benefit to thinking through what is presented in a book like this over solving general problems in a day-to-day context?

Please find something you love doing and learn more about that instead of picking up random things.

What if what you love doing is picking up random things ;)

Re: Algorithms, by Jeff Erickson

#115
I have been reading through these and find them really unique in a good way. I got a new perspective on a lot of stuff I already studied I have a Bachelors in CS and graduated 1.5 years ago.

It doesn't feel formal like a textbook and yet doesn't sacrifice on the mathematical rigor. I would be trying out the exercise problems which seem equally daunting but fun.

I also submitted an issue request on Github and Jeff I have a few questions for you that I put on Quora, I have A2A'd you.

Lastly, thanks for taking the time out and putting content like this out for free. It helps millions of autodidacts like me.

Re: Algorithms, by Jeff Erickson

#117

Does anyone have any impressions on how this compares to CLRS? ( https://en.wikipedia.org/wiki/Introduction_to_Algorithms )

By Ctrl+F'ing, I find 5 mentions of the word "master", none of which are the master theorem. I prefer this to CLRS as, while it's a neat trick, it tends to result in a bunch of people memorising the cases (and taking a "because the book told me to" level of understanding away from that part of the course).

Re: Algorithms, by Jeff Erickson

#118
post #9

Isn’t this the guy that is famous for being admitted to a PhD program with an exceptionally low GPA? If so, why is he the exception and why aren’t more PhD programs looking for non-traditional talent? Edit: I read his blog post. It gave me more insight. It looks possible for people with those sort of grades to be admitted even today, but they seem to need a cheerleader on the inside that will help them.

Yes, that's me. Admissions committees are looking for evidence of future success. Admitting applicants with spotty (not merely "nontraditional") backgrounds is risky -- they might be a diamond in the rough, or they might really be a weak student. And (at least departments like mine) there are far too many applicants with stellar backgrounds to justify taking that risk. At least, that's the usual argument.

What advice would you give to undergraduates that are interested in getting a Ph.D who don't have the best of grades?

Re: Algorithms, by Jeff Erickson

#119

Jeff Erickson was my algorithms professor in 2012. He exemplifies the articulate, passionate educator that I wish I had for my other CS subjects. I recognize many of these notes having read them many times in preparation for quite difficult exams - a fun anecdote shared among people who've taken the class is the 25% credit given on any exam question just for writing "I don't know", effectively a reward for acknowledg…

I've also taken his class and can attest to his subject matter expertise and excellent teaching style

Me too. His notes are amazing in my opinion, and I’m really excited to read some of this book that I didn’t cover during my classes.

I prepped for all of my interviews by just reviewing these notes, and it seemed to work really well.

Re: Algorithms, by Jeff Erickson

#120

Earlier quoted context omitted.

>25% credit given on any exam question just for writing "I don't know", effectively a reward for acknowledging your own shortcoming and for saving the TA the time to decipher a bullshit answer. That’s brilliant, yet I’ve never heard of it. Should be standard scoring for written exams.

This is functionally equivalent to being given negative marks for getting answers wrong, which I've seen on multiple choice tests.

Only if no partial credit is offered, which is not how his exam[0] reads to me:

    As usual, answering any (sub)problem with “I don’t
    know” (and nothing else) is worth 25% partial credit. 
    Yes, even for problem 1. Correct, complete, but
    suboptimal solutions are always worth more than 25%. 
    A blank answer is not the same as “I don’t know”
[0] http://jeffe.cs.illinois.edu/teaching/algorithms/hwex/s18/fi...
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