
A set of top Computer Science blogs - johndcook
http://drtomcrick.wordpress.com/2012/05/07/a-set-of-top-computer-science-blogs/
======
mjn
A few others:

Machine Learning (Theory), <http://hunch.net/>, is a good place to learn about
new machine-learning papers. It doesn't really do research exposition on the
blog, but it posts about recent ML conferences, highlighting some of the
papers the author finds interesting.

Embedded in Academia, <http://blog.regehr.org/>, is about 50% personal stuff,
but 50% posts on John Regehr's work on C-compiler fuzzing, with some
interesting examples if you're into compilers or the finer points of C
semantics.

Proper Fixation, <http://www.yosefk.com/blog/>, is by an embedded developer
(not academic), and not always about research, but it has some good researchy
and expository posts. For example, it has the best concise overview I've found
of how SIMT/SIMD/SMT relate ([http://www.yosefk.com/blog/simd-simt-smt-
parallelism-in-nvid...](http://www.yosefk.com/blog/simd-simt-smt-parallelism-
in-nvidia-gpus.html)).

While it's a mathematics blog, Terence Tao's blog,
<http://terrytao.wordpress.com/>, has a lot of content likely of interest to
computer scientists as well. In particular, his blog-exposition versions of
papers are often a better introduction to recent research for nonspecialists
than anything in the official published literature is.

Tomasz Malisiewicz's computer-vision blog, <http://quantombone.blogspot.com/>,
has intermittent but often quite good posts on object recognition and similar
topics.

Of course I can't refrain from mentioning my own quasi-blog,
<http://www.kmjn.org/notes/>, though only about 1/4 of it is on computer
science (about 4/5 of my day job is computer science, but online essays end up
being mainly an outlet for everything else).

------
mindcrime
For anybody looking to overdose on CS topics, you might also enjoy:

<http://www.reddit.com/r/compsci/>

and

<http://www.reddit.com/r/compscipapers>

Also, <http://machinelearning.reddit.com> and <http://semanticweb.reddit.com>
feature some high quality links and discussion that many HN'ers might find of
interest.

~~~
Homunculiheaded
Unfortunately I would recommend against all of these (except /r/compscipapers,
only because I've never checked it out).

/r/compsci is, in my experience, mostly lower level undergrads who really want
to show how much they know, there's a lot of misinformation in comments that
gets voted up, and a lot of missing nuance in any of the discussions.

/r/semanticweb is very inactive, almost no discussion

/r/machinelearning is pretty poor as well, better choices are
<http://metaoptimize.com/qa> <http://blog.kaggle.com/category/how-i-did-it/>
and following ml topics on quora

~~~
mindcrime
The value there, IMO, is more the links than the discussion. It's not so much
like HN, where the discussion itself is half (or more) of the value. But, for
a quick, concise list of new links in those fields, I find those Reddits all
very valuable.

 _better choices are<http://metaoptimize.com/qa>
<http://blog.kaggle.com/category/how-i-did-it/> and following ml topics on
quora_

Yes, those are excellent sites as well. There are also some good StackExchange
sites that can help one get their fill of CS'y topics.

------
Symmetry
One of the CS blogs I read is Embedded in Academia, which has lots of posts on
C compilers, what they optimize and where they can break

<http://blog.regehr.org/>

~~~
timtadh
I would also add Matt Might's blog <http://matt.might.net/articles/> we see
articles from it on HN from time to time so you may already be familiar with
it.

------
stungeye
Knowing and Doing, reflections of an academic and computer scientist:
<http://www.cs.uni.edu/~wallingf/blog/index.html>

------
brewerja
I really enjoy Eli Bendersky's posts: <http://eli.thegreenplace.net/>

------
lunchladydoris
I must be an idiot. It took me a few Google searches and finally stumbling on
it by accident to figure out how to subscribe to the RSS feed for Serious
Engineering's dynamic Blogger blog, since the "Subscribe to this page..."
option isn't available. In case you too struggle, there's a pop-out menu on
the right.

And now back to ramming crayons up my nose.

~~~
mjn
Many RSS readers these days are pretty good at feed discovery if you just give
them the blog URL. At least, both Google Reader and Newsblur
(<http://www.newsblur.com>) seem to be able to dig up a feed for anything I've
thrown at them.

------
Homunculiheaded
The "How I did it"[0] section of Kaggle's "No Free Hunch" blog is really great
for getting practical insights into solving machine learning problems. All the
posts are short, and unless you're an expert in ML, will likely give you leads
all a lot of new material to learn. The pragmatic bent is what really makes it
such an excellent resource, there's a huge gap between the mathematical
foundations of ML and the solving real world problems side of it.

0\. <http://blog.kaggle.com/category/how-i-did-it/>

------
naerisot
I like Scott Aaronson's blog (<http://www.scottaaronson.com/blog/>), which has
some posts about computational complexity and quantum computing.

------
abhaga
A good source of NLP goodness is <http://nlpers.blogspot.in/>, written by Hal
Daume, a CS prof at UMD. He covers recent NLP conferences and also his own
work. Some of it is in the area of domain adaptation which is of interest to
anyone trying to bring research papers to real world products.

------
possible
Another:

Math ∩ Programming <http://jeremykun.wordpress.com>

He is at the beginning of his academic career (PhD student), but the posts are
especially clear and well-written.

------
josefonseca
Well, just yesterday I thought to myself: I should compile a good list of
blogs for reference, instead of the usual marketing blogs disguised as
Compsi(most of them are really just trying to sell you something, not discuss
real CS). Thanks for sharing.

------
Ironballs
The Theory of Computing blog <http://feedworld.net/toc/> is an aggregator
about theoretical CS stuff.

------
drtomcrick
Excellent, thanks for the extra blog links!

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Bharath1234
Great resources !! Thanks :)

------
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