derek | Shared With: Everyone - Feb 28 2008 | internet, software, web, netflix, machine learning, algorithms, psychology, cool
derek | Shared With: Everyone - Feb 15 2008 | google, algorithms, politics, obama, funny
Obama on algorithms ... gotta be the first time any political candidate has used the term "bubble sort", EVER.
Quoted: The proceedings at Google are not unremittingly serious affairs. Mr. Schmidt asked Senator McCain, “How do you determine good ways of sorting one million 32-bit integers in two megabytes of RAM?” Immediately signaling that the question was asked in jest, Mr. Schmidt moved on. Six months later, Senator Obama faced the same question, but his staff had prepared him. When he replied in fluent tech-speak (“A bubble sort is the wrong way to go”), the quip brought down the house.
derek | Shared With: Everyone - Aug 16 2007 | c#, ai, imaging, algorithms, learning, svm
derek | Shared With: Everyone - Jun 09 2007 | diff, patch, match, algorithms, open source
derek | Shared With: Everyone - Mar 01 2007 | quicksort, algorithms, c#, linq
Side-effect free QuickSort in C# 3.0 (Linq).
Quoted: How often do you write code that just works? It seems to happen so rarely that I find myself suspicious if code does just work. When was the last time that you wrote a non-trivial program that had no compile errors on the first try and then ran fine as
derek | Shared With: Everyone - Feb 23 2007 | video, google, cuckoo hashing, hashing, algorithms
click to playQuoted: We will see improved results on search using hashing and sketching. Hashing is often ... all » analyzed as balls being thrown into bins where you think of the hash items as balls and buckets as bins. By studying variants of the balls and bins processes we obtain a hashing algorithm with 85% hash table space utilization. We will also study locality sensitive hashing, a hashing method used for nearest neighbor search, as opposed to exact search. A locality sensitive hash function is likely to map nearby elements to the same bucket. We will see a variant of locality sensitive hashing that finds an approximate nearest neighbor in high dimensions using linear space. We will also see some lower bounds and applications to kd trees.
derek | Shared With: Everyone - Jun 21 2006 | books, ebooks, algorithmsMore free ebooks.
derek | Shared With: Everyone - Mar 21 2006 | c++, libraries, stl, algorithms
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