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Name: Vamsi
Type: User
Bio: Less jargon and more provable, correct, efficient algorithms.
Name: Vamsi
Type: User
Bio: Less jargon and more provable, correct, efficient algorithms.
A numerically robust computational geometry library for fundamental map overlay algorithms.
Boost.org polygon module
Given a weighted bipartite graph G =(U,V,E) and a non-negative cost function C = cij associated with each edge (i,j)∈E, the problem of finding a match M ⊂ E such that minimizes ∑ cpq|(p,q) ∈ M, is a very important problem this problem is a classic example of Combinatorial Optimization, where a optimization problem is solved iteratively by solving an underlying combinatorial problem. This problem is also known as the assignment problem. The techniques developed in the Hungarian method assumes that the representation of the underlying bipartite graph is dense and thus emphasizes on the asymptotic complexity of computing the shortest augmenting path which is O((|V|+|U| +|E|)log(|V|+|U|)). However in practice this worst case asymptotic bound was never hit especially in case of the sparse representation of the underlying bipartite graph. In practice we found that the runtime (cputime) of the algorithm is dominated by the time to update the dual variables rather than the time to compute the shortest augmenting path. In the original algorithm techniques to update the dual variables are ignored totally and hence the updating of the dual variables need an asymptotic time of O(|U|+|V|+|E|) , in this work we update the dual variables only in O(|V|+|U|) thus improving the performance of solving the assignment problem by a great extent. We encountered this problem in the context of building efficient numerically stable linear solvers which solve equations of the form Ax = b. It has been an accepted fact that permuting the matrix A so that the elements along the diagonal of A are large is a desired property. Weighted bipartite graph matching is used extensively to permute the row/column's of the matrix A so that its closely diagonally dominant.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.