Multilayer Perceptron

Headlines · 2

1. 6d
   KS3 benchmark reports faster convergence than MLP at similar GPU latency

   Independent researcher u/1ncehost compared the third version of K-Splanifolds, KS3, with multilayer perceptrons and earlier KS versions while fitting a 4D Mandelbulb through gradient descent on random samples. The author reports that KS3 converged faster and had nearly identical GPU latency to an MLP. The author also says KS3 ranged from considerably faster convergence than an MLP in areas including noise removal, geometric fitting and financial prediction to roughly equal performance for large language models. These are self-reported results that have not been independently verified.

   r/MachineLearning · 🔥 0
2. 6d
   PBT rescued grokking but did not speed it up

   A Reddit experiment tested Population Based Training (PBT) on modular addition mod 97 using a small MLP, with learning rate and weight decay adapted across 20 members. In a reported “dead zone” where no fixed setting grokked, fast PBT succeeded in 3 of 3 runs at about 6,850 steps, while fixed and slow PBT succeeded in 0 of 3. Under equal compute, however, the best fixed grid cell reached 95% validation accuracy in 317 ± 29 steps, compared with 2,667 ± 2,244 for PBT.

   r/MachineLearning · 🔥 0

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