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Revolutionary Algorithm Boosts Neural Network Training by 50%(alexcoding.com)

250 points by alex_coding 1 year ago | flag | hide | 14 comments

  • john__doe 1 year ago | next

    This is an amazing breakthrough! I wonder how much more efficient our models will become.

    • code_monk 1 year ago | next

      I agree, but we should also consider whether this can lead to overfitting.

  • ai_enthusiast 1 year ago | prev | next

    This algorithm seems to be a major game changer. Can someone share the research paper?

    • researcher_xd 1 year ago | next

      @ai_enthusiast Here's the link to the research paper: [url to paper]

  • ml_engineer 1 year ago | prev | next

    I've read the paper and implemented this algorithm. I can confirm it works like a charm and the neural network training speed has significantly increased.

    • data_samurai 1 year ago | next

      I'm curious, did you encounter any challenges during implementation?

      • ml_engineer 1 year ago | next

        @data_samurai I did face some challenges, especially

        • numpy_guru 1 year ago | next

          Having similar implementation troubles here. Could @ml_engineer share any tips on how they resolved the challenges?

          • ml_engineer 1 year ago | next

            @numpy_guru @data_samurai The major challenge was getting the gradients to work correctly. You'll need to ensure that the learning rate is appropriate. I recommend using a learning rate scheduler too.

  • optimizer_wizard 1 year ago | prev | next

    It would be awesome if this algorithm could be integrated into common deep learning libraries like TensorFlow and PyTorch.

  • keras_user 1 year ago | prev | next

    I heard there's a Keras implementation available here: [url to Keras implementation] just released.

  • pytorch_fan 1 year ago | prev | next

    As for PyTorch users, there's an unofficial implementation available here: [url to PyTorch implementation].

  • stats_prof 1 year ago | prev | next

    • performance_junkie 1 year ago | next

      @stats_prof I'd love to see some extensive benchmark tests between the current state-of-the-art and this revolutionary