9 papers · 1 filter
From Schema to Signal: Retrieval-Augmented Modeling for Relational Data Analytics
Lingze Zeng, Shaofeng Cai, Changshuo Liu +3
Relational data stored in RDBMS is foundational to many real-world applications across domains such as e-commerce, finance, and sociality. While deep neural networks (DNNs) have ac…
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…
Towards Effective Orchestration of AI x DB Workloads
Naili Xing, Haotian Gao, Zhanhao Zhao +6
AI-driven analytics are increasingly crucial to data-centric decision-making. The practice of exporting data to machine learning runtimes incurs high overhead, limits robustness to…
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,…
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…