Science

A new approach leverages the Linux kernel’s ftrace function graph tracer and machine learning to identify subtle system behaviors, including the detection of encryption activity.

Researchers have developed a novel algorithm that tackles long-term decision-making in offline reinforcement learning, improving performance on challenging datasets.

Designing effective reward functions remains a critical challenge in reinforcement learning, and this review explores novel approaches to crafting dense rewards that accelerate agent training and improve performance.

A new approach to maritime anomaly detection leverages federated learning to identify unusual vessel movements while preserving data privacy and reducing communication overhead.

From simple linear models to the power of deep learning, this review offers a complete exploration of techniques for understanding relationships in data.

A new approach to time series prediction leverages a streamlined transformer model and targeted feature selection to improve accuracy in volatile cryptocurrency markets.

Researchers are moving beyond superficial visual cues to identify deepfakes by focusing on subtle inconsistencies in facial movements and temporal artifacts.

A new framework combines the power of graph neural networks with pattern analysis to build more transparent and reliable graph-based artificial intelligence.

A new study pits traditional feature engineering against deep learning to determine the best approach for automatically assessing the condition of valuable Saint-Gaudens Double Eagle coins.

A new framework, Arbitrage, dramatically improves the efficiency of large language models by intelligently switching between draft and refined text generation.