7 papers
NeurBench: A Benchmark Suite for Learned Database Components with Drift Modeling
Zhanhao Zhao, Haotian Gao, Naili Xing +5
Learned database components, which deeply integrate machine learning into their design, have been extensively studied in recent years. Given the dynamism of databases, where data a…
Modeling Concurrency Control as a Learnable Function
Hexiang Pan, Shaofeng Cai, Tien Tuan Anh Dinh +4
Concurrency control (CC) algorithms are important in modern transactional databases, as they enable high performance by executing transactions concurrently while ensuring correctne…
NeurIDA: Dynamic Modeling for Effective In-Database Analytics
Lingze Zeng, Naili Xing, Shaofeng Cai +4
Relational Database Management Systems (RDBMS) manage complex, interrelated data and support a broad spectrum of analytical tasks. With the growing demand for predictive analytics,…
Generative AI for Healthcare: Fundamentals, Challenges, and Perspectives
Gang Chen, Changshuo Liu, Gene Anne Ooi +7
Generative Artificial Intelligence (GenAI) is taking the world by storm. It promises transformative opportunities for advancing and disrupting existing practices, including healthc…
In-Context Adaptation to Concept Drift for Learned Database Operations
Jiaqi Zhu, Shaofeng Cai, Yanyan Shen +3
Machine learning has demonstrated transformative potential for database operations, such as query optimization and in-database data analytics. However, dynamic database environment…
HAKES: Scalable Vector Database for Embedding Search Service
Guoyu Hu, Shaofeng Cai, Tien Tuan Anh Dinh +4
Modern deep learning models capture the semantics of complex data by transforming them into high-dimensional embedding vectors. Emerging applications, such as retrieval-augmented g…