The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...
Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling ...
Google researchers introduce ‘Internal RL,’ a technique that steers an models' hidden activations to solve long-horizon tasks ...
Abstract: With the rise of e-commerce, personalized recommendation algorithms have received much attention in recent years. Meanwhile, multimodal recommendation algorithms have become the next ...
Objectives: This study aims to investigate the efficacy of unsupervised machine learning algorithms, specifically the Gaussian Mixture Model (GMM), K-means clustering, and Otsu automatic threshold ...
Abstract: Specific Emitter Identification (SEI) plays a vital role in the fields of electromagnetic spectrum management and electronic warfare. However, existing SEI algorithms typically require ...
ABSTRACT: An ancient fossil fuel, oil is a crucial energy source for various daily activities, such as electricity generation and vehicle operation. However, its ship transportation poses a ...
Supervised learning relies on historical, labeled data to train algorithms for specific outcomes. This approach is widely used in the financial sector, where reliable past data can guide future ...