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MIT’s Introduction to Algorithms, Lecture 12: Skip Lists - good coders code, great reuse
looks interesting. I might have gotten more out of that skip list talk at WSDM the other year if I'd known about them before.
UM Testudo | CMSC651 Analysis of Algorithms
three of three. I loved 451, and Kruskal's a good professor.
Gregable.: Reservoir Sampling
the more interesting case is streaming skewed reservoir sampling - when you want your sample to be skewed towards the most recent entries in the stream
Want to Remember Everything You'll Ever Learn? Surrender to This Algorithm
"The right time to practice is just at the moment you're about to forget."
Notional Slurry » Search algorithms
good essay on genetic algorithms, and how to search for an optimal algorithm
Real world performance of association rule algorithms - CiteSeerX
More importantly, we found that the choice of algorithm only matters at support levels that generate more rules than would be useful in practice.
Eternally Confuzzled - Red Black Tree Tutorial
pretty good tutorial. should finish it some time.
Datawocky: More data usually beats better algorithms
"To sum up, if you have limited resources, add more data rather than fine-tuning the weights on your fancy machine-learning algorithm. Of course, you have to be judicious in your choice of the data to add to your data set."
That about wraps it up
he talks about how to use the y combinator to replace callcc and exceptions, but he doesn't cover the case of multi-level escape, which both are good for.
Tv's cobweb: Incremental mapreduce
interesting idea. not sure how well it'd work with generalized algorithms.
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