Large Scale Data

Large-scale data analysis focuses on developing efficient methods to process and extract insights from massive datasets exceeding the capacity of traditional computational resources. Current research emphasizes dimensionality reduction techniques like multidimensional scaling and autoencoders, along with online learning and federated learning approaches to handle continuous data streams and address privacy concerns. These advancements are crucial for diverse fields, enabling progress in areas such as medical imaging, climate modeling, and video authenticity verification, where the sheer volume of data previously hindered analysis.