A free-as-in-speech as well as -beer textbook of data structures, covering a great range, including some I hadn't heard of before. Here's the full list: ArrayStack, FastArrayStack, ArrayQueue, ArrayDeque, DualArrayDeque, RootishArrayStack, SLList, DLList,
SEList, SkiplistSSet, SkiplistList, ChainedHashTable, LinearHashTable, BinaryTree, BinarySearchTree, Treap, ScapegoatTree, RedBlackTree, BinaryHeap, MeldableHeap, AdjacencyMatrix, AdjacencyLists, BinaryTrie, XFastTrie, and YFastTrie

Stream summary, count-min sketches, loglog counting, linear counters. Some nifty algorithms for probabilistic estimation of element frequencies and data-set cardinality (via proggit)

Michael Barker and Martin Thompson's talk at the last QCon on the LMAX Disruptor, and other nifty lock-free techniques and patterns. 'Martin Thompson and Michael Barker explain how Intel x86_64 processors and their memory model work, along with low-level techniques that help creating lock-free software.'

TBH, I think this discussion thread is more useful than the article itself. It's still remarkably difficult to successfully apply ML techniques to real-world problems :(

Quite a lot of work for an extra 5% ;)

Detect near-duplicates; would be good for future Razor-like efficient near-duplicate detection. (slides)

'I digested a number of MapReduce patterns and algorithms to give a systematic view of the different techniques that can be found in the web or scientific articles. Several practical case studies are also provided. All descriptions and code snippets use the standard Hadoop’s MapReduce model with Mappers, Reduces, Combiners, Partitioners, and sorting.'

some reasonably good answers on using an LFSR or LCG to generate a full-cycle permutation with no repeats

nice algorithm. requires that the permuted set's size be a power of 2 however - although for smaller sets you can just skip to the next output value, since they're not going to repeat

'a probabilistic data structure conceptually similar to a Bloom filter, but with a more compact in-memory representation, and a slower query time.' could come in handy

huh, I'd never heard of sorting networks before

interesting discussion 

Great comments -- the Burrows-Wheeler Transform is crazy stuff

good to know (via Jeremy)

algorithm to perform set membership tests on enumerated sets quickly and memory-efficiently, using multiplication by primes. Nice trick

really interesting parallel algorithm concepts. I'd seen parallel merge sort before from the map-reduce world, but some others are new to me and worth thinking about (via Hacker News)

in the style of BBC Radiophonics Workshop, with copious flange -- my favourite is heap sort. this is brilliant (via jwz)

some gems here

neat search algo, via Jeremy Zawodny; can be more efficient than binary search (O(log log n)), for indexed, ordered arrays, at the cost of more computation per iteration

just *male* genitalia, mind. I dread to think of what the training corpus looks like

interesting

good reviews and notes from Peteris Krumins

quadtrees, Hilbert curves, and geohashing, as seen in Google's new Closure library. useful for multidimensional addressing in general

course notes from a 4-day MIT course on tech interviewing (via Hacker News)

lovely run-through of the computer-vision algorithms this iPhone app uses (via Waxy)

wow, sounds good! looking forward to this hitting production-ready status