Now ,I need to compare the community detection algorithm performance. I can't find the information about the time complexity of the 'Conductance' and the ‘Modularity’. Could someone please tell me?
Now ,I need to compare the community detection algorithm performance. I can't find the information about the time complexity of the 'Conductance' and the ‘Modularity’. Could someone please tell me?
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This is a good attempt by adding classified information, what else can be improved?
I am trying to calculate the throughput for TCP/MPTCP by using the parameter tp->packets_out and also tp->snd_una but they are not accurate.
How does wireshark do it?
Or does anyone know any solution?
Thanks in advance.
I am the author of https://github.com/teto/mptcpanalyzer which tries to provide some statistics for MPTCP connections. Current release has many bugs but the upcoming one is much better. Feel free to open issues there if you have any problem.
I'm running some performance sensitive code and looking to improve speed. I am using vnormdiff and findmax a lot and wondered whether these are the most efficient functions around? Any thoughts greatly appreciated.
Whenever you encounter a performance problem, it's good to look at your problem from two angles. First, is my overall algorithm the best it can be? If you're using an O(N^2) algorithm but an O(N) is available, that could make an enormous difference. It sounds like you're examining neighbors, so some of the more refined nearest-neighbor algorithms (which depend on dimensionality) might be of assistance.
Second, no discussion about optimization can really get started without profiling information. There's documentation on Julia's profiler here, and a graphical tool for inspecting it here.
Given a query log of about 10 million queries I have to write a program that will ask query from the user and display most similar 10 queries to the input query as a output. Also in case of spelling mistakes it may suggest the correct spellings.
In this context I have studied a few tutorials on Locality Sensitive Hashing but can not understand how can I apply it in this problem. First I was thinking of sorting the log lexicographically. But I don't think it will be good idea to sort the log as far as size of the log is concerned as it may not be efficient to load the whole log into memory.
So can please anyone suggest me any idea to approach the problem. Thank you.
You would definitely want to look at this if you want to parallelize the processing. Minhash Clustering in Mahout
Generate shingles (n-grams with appropriate n)
Generate MinHash
Run LSH
Very detailed information on LSH can be found here: Mining Massive Datasets
Can anyone explain what is the math/physics behind this popular PSP game Locoroco. My understanding about this game collision mechanism is , the whole world is made with bezier curves? If yes - my question is how to build a such a huge endless level , character of these game I guess its blob physics?
Is it tile based level? Please help where to start the research on this topic.
http://www.gotoandplay.it/_articles/2003/12/bezierCollision.php
Vertex level/specific physics with some optimized triangulation algorithm would be my approach.
If you are looking into making a similar game as Locoroco I'd use google to get my answers. A fast search gave me this.
http://www.allegro.cc/forums/thread/587860