Until just five days ago, our repository had very few randomized algorithms. If anyone is motivated, they can dive into the topic and implement some interesting randomized algorithms. These algorithms ...

This paper proposes a Random Forest grid fault prediction model based on Genetic Algorithm optimization (GA-RF) to classify the grid fault types, which improves the distribution network fault ...

The proposal suggests implementing a shared random algorithm to eliminate Maximal Extractable Value (MEV) at the block level and distribute block construction more equitably across the network.

In terms of intelligent driving, the adversarial example of an attack against traffic signs will cause the vehicle to make wrong judgments and decisions. However, the existing adversarial examples of ...

Randomized algorithms are efficient tools for handling big data tensors. They accelerate decomposing large-scale data tensors by reducing the computational complexity of deterministic algorithms and ...

It wasn’t until 2002 that three researchers found a way to de-randomize primality testing, and in practice their algorithm is far slower than the best randomized algorithms. For other problems, it’s ...

Data enhancement methods are methods that an attacker performs a series of transformations on a sample before entering a model to enhance transferability. DI-FGSM (Xie et al., 2019) improves the ...