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Hi algorithm fans! I have problem to solve which is classified as combinational optimization problem. I do not have any background about this technique. Does anyone know any source, tutorial, article where I can learn this technique?
From wikipedia :
In applied mathematics and theoretical computer science, combinatorial optimization is a topic that consists of finding an optimal object from a finite set of objects.
The finite set of objects can be really big and it would take an infinite time to your program to find the solution.
For most of these problems there is no 'technique'.
I would advise reading the wikipedia article on combinatorial optimization, then look at links such as complexity therory (and complexity class P NP ), and very common examples such as the Travelling salesman problem.
Hope it helps
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I'm mainly a selftought I started studying computer science half a year ago.
Before studying, I genneraly just tried to think of an algorithm to do the tasks I needed to be done - with sorting algorithms for example this was quite easy (they might not have been super efficient, but they did good enough). But sometimes I really struggled to come up with algorithms for quite typical problems:
One example for this is triangulation.
The problem is: I didn't know it was called like that. Quite a few hours later I finally found out about delauney triangulation, and all my problems where immediately solved.
Also in computer science I'm learning about a lot of specific algorithms, but my question is:
Is there a way to learn about all these "important" algorithms, maybe by type or something simular? Or is the only good way to keep studying and hope they come my way at some point?
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I am new to algorithms. What is the difference between the design of algorithms and the analysis of algorithms?
The design of an algorithm is the process of inventing the algorithm. You work out what steps to take, the order in which to take them, etc. (Think of it like writing the code for the algorithm). The analysis of an algorithm is where you work out mathematically how efficient it is, prove that it's correct in all cases, etc.
Think of the design as writing the code and the analysis as justifying why that code works and why it's efficient.
Algorithm Design is a specific instructions for completing a task.
They've also been called "recipes".Perhaps a more accurate description would be that algorithms design are patterns for completing a task in an efficient way.
Analysis of Algorithms is the determination of the amount of resources (such as time and storage) necessary to execute them.usually described as (time complexity) and storage locations (space complexity) of an algorithm and stated as a function relating the input length to the number of steps.
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I am a novice to algorithms and data structures. I recently started participating on codeforces and spoj etc.for solving questions i need to study dp,greedy algorithms,graph algorithms,data structures.what should be my strategy for studying or rather sequence and what data structures i need to know for competitive programming?
All in all there shouldnt be an "optimal" sequence. Its all about understanding the topic. Since not two people can learn with the same speed, there shouldnt be something like an "optimal" sequence. But its good to learn basic approaches of each topic.
There are alot Tutorials out there, which explains the most fundamental thing in any topic. E.g. Youtube covers most graph problems. Even DP and so can be found there. Especially on Topcoder Tutorials there is alot you can learn.
On the other hand you will learn nearly nothing, if u dont have to think for yourself. So solving such puzzles is a must. I would recommend this site (especially for dp). Just check the "problem set" link on the site and look for dynamic programming.
I recommend you this book: Competitive Progamming, by Halim. Is very complete, and newbie-compatible.
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I am in a quest of understanding majority of important algorithm that SO community has used in read world applciations. I know a ready list can be extracted from wiki page. But, i am interested only those algorithm or problem that community has faced either in their projects or asked in interviews. Few lines on that algorithm will also be helpful.
I am looking beyond the generic algorithm D&C, DP, Greedy...
If you are interesting about optimization problems which can be used any computer applications such as network and socket programming these could be useful for you;
NearbyNeighbour
Munkres
Hungarian
BruteForce
Min&Max Finding Algorithms
Ant and Bee Colonies Algorithms
General Genetic Algorithm etc.
I totally advice you to search all aboves but genetic algorithms and ant colonies algorithm are asked many interviewers.
I hope that helps.
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I'm currently working on a recommendation system that uses collaborative filtering. And now I'm researching for a good/efficient algorithm that is geared towards movie recommendation. I'm confused because there are many algorithm like the Pearson Correlation Coefficient. And so I don't know what to use/implement.
Can you give me a good/efficient algorithm? or a site that gives a good example or simulation to the algorithm?
Thanks for the help!
Give this paper about the netflix prize a read Netflix Prize. Usually the 'state of the art' is some variant of matrix factorisation such as OrdRec. Check out the Funk Blog FunkSVD which will give you a nice simple explanation about implementing the starts of a matrix factorization technique for CF.
Matrix factorisation (An example in Python) is a good starting point. Furthermore, I'd recommend Ed Chen's Blog and The Mining of Massive Datasets as good introductions to the variety of methods used to solve this type of problem. The interesting thing for me having worked with this type of data is the amount of sparseness, there are of course practical limits, papers by Emmanual Candes seem to shed light on this area, excellent advanced work.