Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
Abstract: Post-training quantization (PTQ) has emerged as a practical approach to compress large neural networks, making them highly efficient for deployment. However, effectively reducing these ...
This repository contains the implementation of the granular ball-based feature selection algorithm for multi-label learning, as described in the research paper published in Knowledge-Based Stems. Note ...
Abstract: Microwave Imaging is a key technique for reconstructing the electrical properties of inaccessible media, relying on algorithms to solve the associated Electromagnetic Inverse Scattering ...
State-of-the-art techniques for pavement performance evaluation have attracted considerable attention in recent years. Artificial Neural Networks (ANNs) can simulate the human brain to discover hidden ...
If you need support for a new econometric algorithm or have an idea for an implementation, please submit your request via GitHub Issues. After evaluation, we'll add it to our DEVPLAN for future ...
In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method that aligns memristor hardware's noisy updates with neural network training, ...
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