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Gödel’s Lost Letter and P=NP

Gödel’s Lost Letter and P=NP

Is It Time To Stop Malware—Forever? Rich DeMillo is a theorist who has also been: the head of all computer science research at Bellcore/Telcordia, the first Chief Technology Officer of HP, and the Dean of the College of Computing at Georgia Tech. All this and he has also made important contributions to theory, software engineering, and security. Today I want to talk about computer malware. Just having a name—malware—for worms and viruses is a problem. I’m as mad as hell, and I’m not going to take this anymore! In the beginning there was ARPANET. I recall watching with envy my colleagues, like Anita Jones, check her ARPANET account for messages. Eventually, those of us on the outside, those of us without ARPANET accounts, decided to act. DeMillo, who is a great and fast writer, sat down and wrote a draft of the proposal in a day or two. I have no doubt we would have email today even if Rich and Larry had not started TheoryNet in 1977, but they did create TheoryNet. At the time it seemed a silly joke, but it was not silly.

Jeff Erickson's Algorithms Sadly, this page has become embarrassingly stale. Updated revisions of most notes, along with unedited video captures of several lectures, are indeed available on the web sites of my most recent courses: (You might notice that some of the updated notes look more like book chapters.) Check back this summer for a major update to this page, complete with three more years of homeworks, exams, and lab problems. This page contains lecture notes and other course materials for various algorithms classes I have taught at the University of Illinois, Urbana-Champaign. The notes are numbered in the order I cover the material in a typical undergraduate class, wtih notes on more advanced material (indicated by the symbol ♥) intersprsed appropriately. Each lecture note includes several exercises, and a near-complete archive of my old homeworks, exams, and discussion problems also follows the lecture notes on this page. Feedback is always welcome, especially bug reports. Everything Algorithms Notes

Difference map algorithm Iterations 0, 100, 200, 300 and 400 in the difference-map reconstruction of a grayscale image from its Fourier transform modulus Although originally conceived as a general method for solving the phase problem, the difference-map algorithm has been used for the boolean satisfiability problem, protein structure prediction, Ramsey numbers, diophantine equations, and Sudoku,[1] as well as sphere- and disk-packing problems.[2] Since these applications include NP-complete problems, the scope of the difference map is that of an incomplete algorithm. Whereas incomplete algorithms can efficiently verify solutions (once a candidate is found), they cannot prove that a solution does not exist. Algorithm[edit] The problem to be solved must first be formulated as a set intersection problem in Euclidean space: find an x in the intersection of sets A and B. x ↦ D(x) = x + β [ PA( fB(x)) − PB( fA(x)) ] , fA(x) = PA(x) − (PA(x)−x)/β , fB(x) = PB(x) + (PB(x)−x)/β . D(x) = x + PA(2 PB(x) − x) − PB(x) .

Fetus Business. No, It's Not A Pun Anymore. This Is A Blog For Fetuses. DEAL. What You'll Wish You'd Known January 2005 (I wrote this talk for a high school. I never actually gave it, because the school authorities vetoed the plan to invite me.) When I said I was speaking at a high school, my friends were curious. I'll start by telling you something you don't have to know in high school: what you want to do with your life. If I were back in high school and someone asked about my plans, I'd say that my first priority was to learn what the options were. It might seem that nothing would be easier than deciding what you like, but it turns out to be hard, partly because it's hard to get an accurate picture of most jobs. But there are other jobs you can't learn about, because no one is doing them yet. And yet every May, speakers all over the country fire up the Standard Graduation Speech, the theme of which is: don't give up on your dreams. What they really mean is, don't get demoralized. Which is an uncomfortable thought. I'm not saying there's no such thing as genius. Upwind Ambition Corruption Now

Neopythonic List of NP-complete problems This is a list some of the more commonly known problems that are NP-complete when expressed as decision problems. As there are hundreds of such problems known, this list is in no way comprehensive. Many problems of this type can be found in Garey & Johnson (1979). Graphs and hypergraphs[edit] Graphs occur frequently in everyday applications. NP-complete special cases include the edge dominating set problem, i.e., the dominating set problem in line graphs. Mathematical programming[edit] Formal languages and string processing[edit] Games and puzzles[edit] Other[edit] NP-complete special cases include the minimum maximal matching problem,[71] which is essentially equal to the edge dominating set problem (see above). See also[edit] Notes[edit] References[edit] General Garey, Michael R.; Johnson, David S. (1979), Computers and Intractability: A Guide to the Theory of NP-Completeness, W. Specific problems Friedman, E (2002). External links[edit]

Marginal Revolution Astrónomos descubren “estrellas imposibles” | Desde la Redacción Dos estrellas de tipo enanas rojas que orbitan entre sí cada 2,5 horas, luego se fundirán en una. / Space.comPor Miguel Artime - Lo que los astrónomos acaban de encontrar en nuestra galaxia, la Vía Láctea, es algo que hasta ahora parecía imposible. Estrellas gemelas orbitándose la una a la otra en un ciclo vertiginoso completo de menos de cuatro horas. Hasta ahora, los científicos creían que algo así era imposible, y eso que a pesar de que nuestro sol carece de compañera, casi la mitad de las estrellas de nuestra galaxia podrían formar parte de un sistema binario. Empleando el Telescopio Infrarrojo del Reino Unido (UKIRT) situado en Hawaii, los astrónomos descubrieron cuatro parejas de "estrellas imposibles". Por norma, se creía que si una estrella se formaba demasiado cerca de otra, las dos estrellas se mezclarían rápidamente formando un único astro mayor. Lo que no saben explicar los astrónomos es cómo pudieron reducir su tamaño las órbitas de estas binarias. Fuente Yahoo!

Lectures 1 and 2: Analysis of Algorithms I just finished watching the last lecture of MIT's "Introduction to Algorithms" course. Having a great passion for all aspects of computing, I decided to share everything I learned with you, my dear readers! This is the first post in an article series about this course. As I wrote earlier, I am very serious about watching video lectures. If they are math-intensive, I usually take notes as if I were in the classroom. Lectures in this course were exactly like that -- logarithms, big-o's, thetas, expectations, and all the other math guys fighting with each other on the blackboards. There are totally 23 video lectures, each around 1 hour 20 minutes long. Understanding and designing effective algorithms is a very important skill for a top-notch programmer. Let's start with Lecture 1 of this course. Lecture 1: Analysis of Algorithms The first lecture is given by the famous professor Charles E. He starts the lecture by explaining what this course and algorithms will be all about. Lecture 1 notes:

Home-Page Immediate opening (uupdated August July 8, 2007) for scientific research programmer at Genetic Programming Inc. Last updated July 8, 2007 What is Genetic Programming (GP)? How Genetic Programming Works Sources of Information about the Field of Genetic Programming (GP), Genetic Algorithms (GA), and the Field of Genetic and Evolutionary Computation (GEC) Conferences about Genetic Programming (GP) and Genetic and Evolutionary Computation (GEC) Application Areas for Genetic Programming News about Genetic Programming Parallelization of Genetic Programming John Koza’s Publications on Genetic Programming Websmaster Other Links Genetic programming (GP) is an automated method for creating a working computer program from a high-level problem statement of a problem. Given these results, we say that “Genetic programming now routinely delivers high-return human-competitive machine intelligence.” Genetic programming starts with a primordial ooze of thousands of randomly created computer programs. · For E.

Kenyan Pundit The Internet map Reverse a linked list in java « Think ! If you search for it you will get millions of solutions but sadly (like many things in internet) the first few solutions seem unintuitive and unnecessarily complex for such a simple problem, not sure why, anyway putting mine out there for somebody to point out why I should go for a more complex solution. [in java for a change] Idea : Use two references and reverse their links and proceed till we reach the end public void reverse_iterative { if(isEmpty()) { return;} //curr == null Node currNode,nextNode , loopNode; currNode = head; nextNode = head.next; head.next = null; while(nextNode ! Recursive Idea : Reverse the sublist starting from second node and point the second node to first, apply this recursively. private void reverse(Node curr) { if(isEmpty()) { return;} //curr == null if(curr.next == null) { head = curr; return; } reverse(curr.next); curr.next.next = curr; curr.next = null; } Share This

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