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  • What do I need to know about Data Structures and Algorithms in the "real" world

    - by Ray T Champion
    I just finished the data structures and algorithms course in school , I took it during the summer so 6wks course vs a 16 wk course during the regular semester. So not only was the course hard but it was really really really fast. My question is what do I need to know about data structures in the real world? I understand what they do and how they work, for the most part, but I had a real tough time coding them , I wouldn't be able to write the code for a binary tree class or a balanced tree class from scratch .... Is that bad? should I retake it , or is knowledge of how they work sufficient, without being able to write the classes from scratch?

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  • Stereo images rectification and disparity: which algorithms?

    - by alessandro.francesconi
    I'm trying to figure out what are currently the two most efficent algorithms that permit, starting from a L/R pair of stereo images created using a traditional camera (so affected by some epipolar lines misalignment), to produce a pair of adjusted images plus their depth information by looking at their disparity. Actually I've found lots of papers about these two methods, like: "Computing Rectifying Homographies for Stereo Vision" (Zhang - seems one of the best for rectification only) "Three-step image recti?cation" (Monasse) "Rectification and Disparity" (slideshow by Navab) "A fast area-based stereo matching algorithm" (Di Stefano - seems a bit inaccurate) "Computing Visual Correspondence with Occlusions via Graph Cuts" (Kolmogorov - this one produces a very good disparity map, with also occlusion informations, but is it efficient?) "Dense Disparity Map Estimation Respecting Image Discontinuities" (Alvarez - toooo long for a first review) Anyone could please give me some advices for orienting into this wide topic? What kind of algorithm/method should I treat first, considering that I'll work on a very simple input: a pair of left and right images and nothing else, no more information (some papers are based on additional, pre-taken, calibration infos)? Speaking about working implementations, the only interesting results I've seen so far belongs to this piece of software, but only for automatic rectification, not disparity: http://stereo.jpn.org/eng/stphmkr/index.html I tried the "auto-adjustment" feature and seems really effective. Too bad there is no source code...

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  • Color schemes generation - theory and algorithms

    - by daniel.sedlacek
    Hi I will be generating charts and diagrams and I am looking for some theory on color schemes and algorithm examples. Example questions: How to generate complementary or analogous colors? How to generate pastel, cold and warm colors? How to generate any number of random but distinct colors? How to translate all that to the hex triplet (web color)? My implementation will be in AS3 but any examples in metacode are welcome.

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  • Order of learning sort algorithms

    - by user619818
    I have already studied bubblesort, insertion sort and selection sort and can implement them in C pretty much from knowledge of the algorithm. I want to go on to learn shellsort, merge sort, heapsort and quicksort, which I guess are a lot harder to understand. What order should I take these other sort algos? I am assuming a simpler sort algo helps learn a more complex one. Don't mind taking on some others if it helps the learning process.

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  • Functional programming and stateful algorithms

    - by bigstones
    I'm learning functional programming with Haskell. In the meantime I'm studying Automata theory and as the two seem to fit well together I'm writing a small library to play with automata. Here's the problem that made me ask the question. While studying a way to evaluate a state's reachability I got the idea that a simple recursive algorithm would be quite inefficient, because some paths might share some states and I might end up evaluating them more than once. For example, here, evaluating reachability of g from a, I'd have to exclude f both while checking the path through d and c: So my idea is that an algorithm working in parallel on many paths and updating a shared record of excluded states might be great, but that's too much for me. I've seen that in some simple recursion cases one can pass state as an argument, and that's what I have to do here, because I pass forward the list of states I've gone through to avoid loops. But is there a way to pass that list also backwards, like returning it in a tuple together with the boolean result of my canReach function? (although this feels a bit forced) Besides the validity of my example case, what other techniques are available to solve this kind of problems? I feel like these must be common enough that there have to be solutions like what happens with fold* or map. So far, reading learnyouahaskell.com I didn't find any, but consider I haven't touched monads yet. (if interested, I posted my code on codereview)

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  • Prefer algorithms to hand-written loops?

    - by FredOverflow
    Which of the following to you find more readable? The hand-written loop: for (std::vector<Foo>::const_iterator it = vec.begin(); it != vec.end(); ++it) { bar.process(*it); } Or the algorithm invocation: #include <algorithm> #include <functional> std::for_each(vec.begin(), vec.end(), std::bind1st(std::mem_fun_ref(&Bar::process), bar)); I wonder if std::for_each is really worth it, given such a simple example already requires so much code. What are your thoughts on this matter?

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  • How do I learn algorithms and data structures?

    - by sushil bharwani
    this is in continuation to my previous question where i asked is it necessary to learn algorithm and datastructures. I feel yes it is. Now when i work in a enviornment where i wont ever get the chance to learn it by experimenting or practically or in any assignment. What is the right approach like the right books, right kind of problems, right kind of resources that i can go through to give six months or a year or two to learn it. And also mould my mind in a way that it can relate problems to datastructures and algos.

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  • Algorithms for pairing a rating system to an assignment queue

    - by blunders
    Attempting to research how to allow a group of people to effectively rank a set of objects (each group member will have contributed one object to the group), and then assign each member an object that's not their own based on: Their ratings of the objects, Their objects rating, and The object remaining to be assigned. Idea is to attempt to assign objects to people based on the groups rating of their contribution to the group relative to other member's contribution, the the personal preferences expressed via the ratings. Any suggestions for: Further research, Refining the statement of the problem/solution, or A solution.

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  • Semantic algorithms

    - by Mythago
    I have a more theoretical than practical question. I'll start with an example - when I get an email and open it on my iPad, there is a feature, which recognizes the timestamp from the text and offers me to create an event in the calendar. Simply told, I want to know theoretically how it's done - I believe it's some kind of semantic parsing, and I would like if someone could point me to some resources, where I can read more about this.

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  • cool project to use a genetic algorithm for?

    - by Ryan
    I'm looking for a practical application to use a genetic algorithm for. Some things that have thought of are: Website interface optimization Vehicle optimization with a physics simulator Genetic programming Automatic test case generation But none have really popped out at me. So if you had some free time (a few months) to spend on a genetic algorithms project, what would you choose to tackle?

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  • Which algorithms/data structures should I "recognize" and know by name?

    - by Earlz
    I'd like to consider myself a fairly experienced programmer. I've been programming for over 5 years now. My weak point though is terminology. I'm self-taught, so while I know how to program, I don't know some of the more formal aspects of computer science. So, what are practical algorithms/data structures that I could recognize and know by name? Note, I'm not asking for a book recommendation about implementing algorithms. I don't care about implementing them, I just want to be able to recognize when an algorithm/data structure would be a good solution to a problem. I'm asking more for a list of algorithms/data structures that I should "recognize". For instance, I know the solution to a problem like this: You manage a set of lockers labeled 0-999. People come to you to rent the locker and then come back to return the locker key. How would you build a piece of software to manage knowing which lockers are free and which are in used? The solution, would be a queue or stack. What I'm looking for are things like "in what situation should a B-Tree be used -- What search algorithm should be used here" etc. And maybe a quick introduction of how the more complex(but commonly used) data structures/algorithms work. I tried looking at Wikipedia's list of data structures and algorithms but I think that's a bit overkill. So I'm looking more for what are the essential things I should recognize?

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  • Would a professional, self taught programmer benefit from reading an algorithms book?

    - by user65483
    I'm a 100% self taught, professional programmer (I've worked at a few web startups and made a few independent games). I've read quite a few of the "essential" books (Clean Code, The Pragmatic Programmer, Code Complete, SICP, K&R). I'm considering reading Introduction to Algorithms. I've asked a few colleagues if reading it will improve my programming skills, and I got very mixed answers. A few said yes, a few said no, and a one said "only if you spend a lot of time implementing these algorithms" (I don't). So, I figured I'd ask Stack Exchange. Is it worth the time to read about algorithms if you're a professional programmer who seldom needs to use complex algorithms? For what it's worth, I have a strong mathematical background (have a 2 year degree in Mathematics; took Linear Algebra, Differential Equations, Calc I-III).

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  • Is there a 'design pattern' type listing of common algorithms?

    - by KevinM1
    Is there a 'design pattern' styled listing of common/popular algorithms anywhere? Specifically, something that has a similar format along the lines of: Algorithm Name: e.g., Quick Sort, Bubble Sort, etc. Problem: A description of the stereotypical problem the algorithm is supposed to address Description: Description of the solution Implementation: Code examples of the solution Big O Rating: Self-explanatory Similar Algorithms: Algorithms that address the same problem in different ways, or similar problems I really like the GoF design pattern listing style, and I think it would help me learn various algorithms better/easier if I could find a resource that was similar in terms of organization.

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  • What problems have you solved using genetic algorithms/genetic programming?

    - by knorv
    Genetic algorithms (GA) and genetic programming (GP) are interesting areas of research. I'd like to know about specific problems you - the SO reader - have solved using GA/GP and what libraries/frameworks you used if you didn't roll your own. Questions: What problems have you used GA/GP to solve? What libraries/frameworks did you use? I'm looking for first-hand experiences, so please do not answer unless you have that.

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  • Traveling Salesman - Nearest Neighbor vs Genetic DEATHMATCH

    - by EvilTeach
    Over the last few days I have noted a few web sites that demonstrated TS solution using genetic algorithms. I am looking for your opinion which is better for this particular problem. Heuristics vs Genetic. By better, I mean will yield a shorter/lower cost path. Explain why you feel the way that you do. Examples, and off-site links are welcome.

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  • Genetic algorithm resource

    - by Siblja
    Lately I'm interested in a topic of genetic algorithms, but i couldn't find any good resource. If you know any good resource, book or a site i would appreciate it. I have solid knowledge of algorithms and A.I. but im looking for something with good introduction in genetic programing.

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  • Don Knuth and MMIXAL vs. Chuck Moore and Forth -- Algorithms and Ideal Machines -- was there cross-pollination / influence in their ideas / work?

    - by AKE
    Question: To what extent is it known (or believed) that Chuck Moore and Don Knuth had influence on each other's thoughts on ideal machines, or their work on algorithms? I'm interested in citations, interviews, articles, links, or any other sort of evidence. It could also be evidence of the form of A and B here suggest that Moore might have borrowed or influenced C and D from Knuth here, or vice versa. (Opinions are of course welcome, but references / links would be better!) Context: Until fairly recently, I have been primarily familiar with Knuth's work on algorithms and computing models, mostly through TAOCP but also through his interviews and other writings. However, the more I have been using Forth, the more I am struck by both the power of a stack-based machine model, and the way in which the spareness of the model makes fundamental algorithmic improvements more readily apparent. A lot of what Knuth has done in fundamental analysis of algorithms has, it seems to me, a very similar flavour, and I can easily imagine that in a parallel universe, Knuth might perhaps have chosen Forth as his computing model. That's the software / algorithms / programming side of things. When it comes to "ideal computing machines", Knuth in the 70s came up with the MIX computer model, and then, collaborating with designers of state-of-the-art RISC chips through the 90s, updated this with the modern MMIX model and its attendant assembly language MMIXAL. Meanwhile, Moore, having been using and refining Forth as a language, but using it on top of whatever processor happened to be in the computer he was programming, began to imagine a world in which the efficiency and value of stack-based programming were reflected in hardware. So he went on in the 80s to develop his own stack-based hardware chips, defining the term MISC (Minimal Instruction Set Computers) along the way, and ending up eventually with the first Forth chip, the MuP21. Both are brilliant men with keen insight into the art of programming and algorithms, and both work at the intersection between algorithms, programs, and bare metal hardware (i.e. hardware without the clutter of operating systems). Which leads me to the headlined question... Question:To what extent is it known (or believed) that Chuck Moore and Don Knuth had influence on each other's thoughts on ideal machines, or their work on algorithms?

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  • Tracking fitness in a genetic algorithm

    - by Chuck Vose
    I'm still hacking on my old ruby for the undead post (I know, I know, stop trying to bring the post back from the dead Chuck). But the code has gotten a little out of hand and now I'm working on a genetic algorithm to create the ultimate battle of living and dead with the fitness being how long the battle lasts. So, I've got the basics of it down; how to adjust attributes of the game and how to acquire the fitness of a solution, what I can't figure out is how to store the fitness so that I know when I've tried a combination before. I've not been able to find much genetic code to look at let alone code that I can read well enough to tell what's going on. Does anyone have an idea how this is normally done or just simply an algorithm that could help point me in the right direction?

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  • Should I keep investing into data structures and algorithms?

    - by 4bu3li
    These days, I'm investing heavily in data structures and algorithms and trying to solve some programming puzzles. I'm trying to code and solve with Java and Clojure. Am I wasting my time? should I invest more in technologies and frameworks that I already know in order to gain deeper knowledge (the ins and the outs) and be able to code with them more quickly? By studying data structures and algorithms, am I going to become a better programmer or those subjects are only important during college years?

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  • Should I keep investing into data structures and algorithms?

    - by Chiron
    These days, I'm investing heavily in data structures and algorithms and trying to solve some programming puzzles. I'm trying to code and solve with Java and Clojure. Am I wasting my time? should I invest more in technologies and frameworks that I already know in order to gain deeper knowledge (the ins and the outs) and be able to code with them more quickly? By studying data structures and algorithms, am I going to become a better programmer or those subjects are only important during college years?

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  • How should I Test a Genetic Algorithm

    - by James Brooks
    I have made a quite few genetic algorithms; they work (they find a reasonable solution quickly). But I have now discovered TDD. Is there a way to write a genetic algorithm (which relies heavily on random numbers) in a TDD way? To pose the question more generally, How do you test a non-deterministic method/function. Here is what I have thought of: Use a specific seed. Which wont help if I make a mistake in the code in the first place but will help finding bugs when refactoring. Use a known list of numbers. Similar to the above but I could follow the code through by hand (which would be very tedious). Use a constant number. At least I know what to expect. It would be good to ensure that a dice always reads 6 when RandomFloat(0,1) always returns 1. Try to move as much of the non-deterministic code out of the GA as possible. which seems silly as that is the core of it's purpose. Links to very good books on testing would be appreciated too.

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