In case you didn't make the connection, this material is by the professor who wrote the recently posted article: "Getting into a PhD program with a low GPA". His undergraduate GPA was a 2.4/4.0, according to his website.
I stumbled upon this today... The page has a link to everything.pdf (http://compgeom.cs.uiuc.edu/~jeffe/teaching/algorithms/every...) which is an 765 page pdf & covers all the material from the course. It can also be a good reference/text book for a self-taught algorithms course.
I second that, I had him in '05 and specifically waited to take the class with him as the teacher. Was well worth it, he brings a sense of humor and style to teaching that turned an otherwise difficult class into an absolute joy.
To wit, I also had Jeff for algorithms a couple years ago and he is indeed a dedicated and passionate teacher. But thank you for your support, fellow HNers!
"Am I writing a textbook? No. All textbooks suck. (Partly that's because of the unethical rapacious profitable business practices of (most) textbook publishers—these notes will always be freely available."
Much inadvertent wisdom in this: If you're a student, you will (usually) learn more from trying to solve a problem and failing than by reading the answer.
CLRS is the classic textbook for Algorithms... For some topics Klienberg and Tardos is good, I will suggest to read the CLRS text and keep K&T for topics you want to read more on, also the K&T problems are much harder (usually) than CLRS.
for their intro algorithms class. I TA'd a semester with this book, and while it definitely has its warts it is much more compact and readable than CLRS.
I'll second Intro to Algorithms, which has been mentioned. It's what I used in my algorithms class and it's quite comprehensive. (It will also take you a while to get through.)
http://news.ycombinator.com/item?id=1072923