I’ve recently gained interest in esoteric algorithms and languages. They are fun to read and write. The most famous one of them is quantum bogosort that I describe below, Quantum bogosort: Assume that you have a deck of cards. If you you have a quantum computer one of the most efficient sorting algorithm will probably [...]
Archive for the ‘Computer Science’ Category
Importance Sampling
19 Jan 2011 at 16:24
caglar
Artificial Intelligence, Computer Science, Engineering, Machine Learning, Mathematics, Programming, science, statistics
Importance sampling is probably one of the easiest sampling algorithm and one of the most fundamental one as well. The main purpose of it is to estimate the properties of a particular distribution, while only having samples generated from a different distribution rather than the distribution of interest. Depending on the application, the term may [...]
Scalability Tips for Building Fast Applications
Optimising code performance is known to be the black art and don’t worry about optimisation until you really need it. Hence don’t forget that, “premature optimisation is the root of evil”. Here are some useful points that you should consider while writing your code: You can really increase the speed of hashing by using fast [...]
Advices to a Beginning Graduate Student
Manuel Blum, a computer scientist in CMU has given a great talk about advices to phd students. There are very nice advices in this talk and they are not only for graduate students but as well as people who like doing research can benefit it. The original source of this article is this talk, I [...]
Hypercomputation
20 Dec 2010 at 21:36
caglar
Artificial Intelligence, complexity, Computer Science, Philosophy, science
You think that anything computable can be computed with a Turing machine. Now forget about Church-Turing Thesis for a while and ladies and gentlemen, here comes the HyperComputers!: Christof Teuscher et al, 2002, Hypercomputation: hype or computation? Copeland and Proudfoo, Alan Turing’s Forgotten ideas, 1999, Scientific American Selim G. Akl, The Myth of Universal computation, [...]
Should implementing ML algorithms banned for Production Systems?
19 Dec 2010 at 17:51
caglar
Artificial Intelligence, Computer Science, Engineering, Machine Learning, Softwares
Nowadays everybody is talking about the how machine-learning algorithms can be useful your business, but now I’ll discuss here how it can harm your business . As a design principle(best practice), for the sake of security-preservation and efficiency in cryptographic systems, implementation of cryptographic algorithms isn’t recommended for production systems when there is already [...]
Perl Poetry
Yeah again I didn’t bother writing a blog-post myself and thereof I’m putting here an interesting fragment from Larry Wall’s big Camel (see: judgin’ a book by its cover) book. The forgery in the attendant sidebar appeared on Usenet on April Fool’s Day, 1990. It is presented here without comment, merely to show how disgusting [...]
Measure Kolmogorov Complexity of a file with the Lazy Man’s technique in *nix
06 Dec 2010 at 20:51
caglar
Artificial Intelligence, complexity, Computer Science, Engineering, Linux, Systems, Web
With the gnu ent command you get the entropy of a file in an easy way. For example: 1 2 3 4 5 6 7 8 9 10 11 12 13 caglar@caglar-desktop:/tmp$ cat /dev/urandom | base64 | head -c 1200 > rand.txt caglar@caglar-desktop:/tmp$ ent rand.txt Entropy = 5.982286 bits per byte. Optimum compression would [...]
Natural Language Programming For Working Developer
30 Nov 2010 at 21:30
caglar
Artificial Intelligence, Cognitive Science, Computer Science, Language Science, Technology
The title explains all the buzz. If you are seeking for a short, brief but an informative introduction to NLP. The following web site is suitable for you. Also that site explains the fundamentals of Haskell in a very approachable way. Link: Natural Language Programming For the Working Programmer Related Posts:Learn you a haskell for [...]
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