Faculty develop methods for structured and unstructured biomedical data that advance statistical inference, machine learning, causal inference, and algorithmic modeling. Their work delivers principled ...

A study on high-concurrency payment systems proposes a distributed architecture with layered consistency control to balance transaction accuracy and scalability. By decoupling system components and ...

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With the emergence of huge amounts of heterogeneous multi-modal data, including images, videos, texts/languages, audios, and multi-sensor data, deep learning-based methods have shown promising ...

Most AI systems are trained on historical data. When conditions shift due to changing consumer sentiment, models trained on ...