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Herring

This has to be the only free CS theory book out there. It comes up way too often.

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I've seen quite a few, actually... many of them on Hacker News.

http://mitpress.mit.edu/sicp/

http://www.cacr.math.uwaterloo.ca/hac/index.html

http://ocw.mit.edu/OcwWeb/Electrical-Engineering-and-Compute...

http://omega.albany.edu:8008/JaynesBook.html

http://research.microsoft.com/en-us/um/people/simonpj/papers...

These are from my own bookmarks... looks like there are a lot more at http://www.reddit.com/r/csbooks/top/?t=all

Wow! The Jaynes book is on the order of 3,000 pages! Looks like a potentially comprehensive reference for all things probability.

Can anyone comment on the quality of the writing?

Jaynes died before he finished it. It's still one of the most important books I ever read.

It's good, with a heavy focus on frequentist statistics and maximum entropy approach

I think to say the book has a heavy focus on frequentist statistics is a little misleading. Jaynes discusses a lot of frequentist methods but the emphasis is on doing so from a very Bayesian point of view.

He uses Bayesian methods in some cases, and non-Bayesian method in others. For instance on page 1412 he describes a problem for which Bayesian methods are "not appropriate." http://omega.albany.edu:8008/ETJ-PS/cc14g.ps

This is a bit of an anathema to purist Bayesians like Radford Neal who say that Jaynes Maximum Entropy method is not consistent with Bayesian methods and that it "doesn't make any sense"

http://groups.google.com/group/sci.stat.consult/msg/2cf57ceb...

More long winded than most, but it's normal "physics" writing. Very clear. I recommend the preface whether or not you intend to read the whole thing.

It's probably pretty good. (Sorry.)

http://www.google.com/search?q=site%3Acs.*.edu+book+draft...

brings up at least two more: http://www.cs.berkeley.edu/~vazirani/algorithms.html

http://www.cs.princeton.edu/theory/complexity/

Of course, both of them also get posted alot =).

The other reason why it comes up so often is that it's damn good.

I love the irony that it's written by a member of the Physics faculty.

Ah, Cambridge.

Machine learning and the like is often done by people outside the computer science department. EE, statistics, math and physics are common.

At Cambridge, you find high-level theoretical machine learning research in the Engineering, Computer Science and Physics faculties. (My spies inside the DAMTP don't point to much going on there - but who knows). None of the above ever seem to talk to each other, sadly.

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