Nowadays Vinay Deolalikar’s claimed proof of p versus np problem is being discussed in many blogs and in many different platforms. And with the light of these discussions, my interests in theoretical computer science and math is awakened . Hence I wanted to write something about mathematics (Although I’m not a mathematician but always have [...]
Posts Tagged ‘Computer Science’
A Theoretical Computer Science Cheat Sheet
I usually don’t like the cheat-sheets because they are so subtle and you’re able to find much more comprehensive information with better explanations on Google. But sometimes all you need to know is a simple formula or a function, which you can get benefit of a cheat-sheet for enough information with less effort. For programming [...]
Scooping the Loop Snooper
Today I’ve just found a great and very strange proof of the halting problem by the famous philosopher and linguist Geoffrey Pullum. It is so simple yet logically accurate. You can also access the original version of this proof from the Geoffrey Pullum’s web page in University of Edinburgh. What makes this proof more interesting [...]
The Basic Semantics of Nominals and Generative Lexicon
06 Mar 2010 at 20:48
caglar
Artificial Intelligence, Cognitive Science, Computer Science, Uncategorized
Generative Lexicon Generative Lexicon is a computational theory of linguistic semantics that focuses on the nature of compositionality. The theory is firstly proposed by James Pustejovsky in 1991 in his paper titled as “The Generative Lexicon”. The Generative Lexicon has 4 levels: 1. Lexical Typing Structure 2. Argument Structure 3. Event Structure 4. Qualia Structure [...]
Network Anomaly Detection
06 Mar 2010 at 20:29
caglar
Artificial Intelligence, Computer Science, Network Engineering, Security, Uncategorized, statistics
Anomaly detection is one of the most important aspect of Network Security Monitoring. Most of the current approaches in Network Intrusion Detection Systems use signature based techniques. Recently data-mining approaches become popular and many paper published about that topic. Supervised data-mining approaches rely on some kind of training data. But for network traffic, it is [...]
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