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.
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).
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...).
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).