A direct optimization test was conducted on a neural network for MNIST image classification. The network features a 784-32-10 architecture with a total of 25,450 continuous parameters (weights and biases). Instead of employing backpropagation or gradient information, the parameters were optimized using MDP, a Derivative-Free Optimization method. ​The objective was to directly minimize the Cross-Entropy Loss on a subset of 5,000 training images. Final evaluations were performed on independent validation and test sets. ​In the best run, MDP achieved an objective loss of 0.0004083, a validation accuracy of 93.7%, and a test accuracy of 93.4%. These results outperform the baseline established by Adam, which achieved a final loss of 0.002945, a validation accuracy of 91.8%, and a test accuracy of 91.7% using the same network architecture. ​Notably, this optimization was successfully performed over a 25,450-dimensional search space, achieving convergence across 1,000,000 function evaluations without relying on gradients or population-based methods. ​The code for this test, along with other Python implementation examples, is available in the examples folder of the official project repository: https://github.com/misa-hdez/sgo-lab submitted by /u/Mis4318 [link] [Kommentare]

A new report suggests the unit, which employs 6,500 people, is on the verge of revolt.

Oof, what a beauty. In the 1960s, four Porsche 912s were customized for use as police cars in Japan. This one, which was used in Kanagawa until 1973, is the

Manage your properties, tenants, and maintenance requests with ease. Free 45-day trial, no credit card required.

Samsung Electronics is reportedly in talks to make a key portion of one of Google's most advanced future artificial intelligence chips. The deal would give the

Anthropic’s leaning in to the whole nanny state thing. …

What is a sequential scan vs index scan vs parallel scan .... and what is a bitmap heap scan? Postgres scan types explained and diagrammed.

$1 makes it 1 pixel bigger. Forever.

Um binário C que faz animações e aplica gradiente colorido em tempo real em banners/caracteres do terminal Windows, Linux, Android - inrryoff/NeonX