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Monday, July 09, 2018

New Parallel Sampling Algorithm for Speed

Nice to see all of the algorithm research does not have to be AI based.    Note the adaptive sampling approach.  A sort of computationally-crowd-sourced idea?   Applications?   Authors: Singer and Balkanski

Breakthrough' Algorithm Exponentially Faster Than Any Previous One 
John A. Paulson School of Engineering and Applied Sciences
By Leah Burrows

Researchers at Harvard University's John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a new algorithm that exponentially speeds computation by dramatically reducing the number of parallel steps required to reach a solution. The new approach allows the researchers to speed computation for an enormously large class of problems across many different fields, including computer vision, information retrieval, network analysis, computational biology, and auction design, among others. "We can now perform computations in just a few seconds that would have previously taken weeks or months," says SEAS researcher Yaron Singer. The new algorithm samples a variety of directions in parallel; based on that sample, the program discards low-value directions and chooses the most valuable ones to progress towards a solution. The researcher was presented at the ACM Symposium on Theory of Computing, June 25-29 in Los Angeles, CA.  ... " 

Also mentioned in IEEE Spectrum with examples:

New Optimization Algorithm Exponentially Speeds Computation
Finding the optimal solutions to complex problems can be dramatically faster  .. By Charles Q. Choi ... " 

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