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- In-crowd_algorithm abstract "The in-crowd algorithm is a numerical method for solving basis pursuit denoising quickly; faster than any other algorithm for large, sparse problems. Basis pursuit denoising is the following optimization problem:where is the observed signal, is the sparse signal to be recovered, is the expected signal under , and is the regularization parameter trading off signal fidelity and simplicity.It consists of the following: Declare to be 0, so the unexplained residual Declare the active set to be the empty set Calculate the usefulness for each component in If on , no , terminate Otherwise, add components to Solve basis pursuit denoising exactly on , and throw out any component of whose value attains exactly 0. This problem is dense, so quadratic programming techniques work very well for this sub problem. Update - n.b. can be computed in the subproblem as all elements outside of are 0 Go to step 3.Since every time the in-crowd algorithm performs a global search it adds up to components to the active set, it can be a factor of faster than the best alternative algorithms when this search is computationally expensive. A theorem guarantees that the global optimum is reached in spite of the many-at-a-time nature of the in-crowd algorithm.".
- In-crowd_algorithm wikiPageID "33668408".
- In-crowd_algorithm wikiPageRevisionID "532452063".
- In-crowd_algorithm hasPhotoCollection In-crowd_algorithm.
- In-crowd_algorithm subject Category:Mathematical_optimization.
- In-crowd_algorithm comment "The in-crowd algorithm is a numerical method for solving basis pursuit denoising quickly; faster than any other algorithm for large, sparse problems.".
- In-crowd_algorithm label "In-crowd algorithm".
- In-crowd_algorithm sameAs m.0hgrprx.
- In-crowd_algorithm sameAs Q6008626.
- In-crowd_algorithm sameAs Q6008626.
- In-crowd_algorithm wasDerivedFrom In-crowd_algorithm?oldid=532452063.
- In-crowd_algorithm isPrimaryTopicOf In-crowd_algorithm.