6 papers
Cache-Aware I/O Cost Modeling for Disk-Based Learned Indexes
Zhanwei Shi, Meng Zhang, Guangyi Zhang +5
Learned indexes have shown attractive space-time trade-offs in main-memory settings, yet a principled I/O cost model for their disk-resident deployments is still missing, which is…
Momentum-integrated Multi-task Stock Recommendation with Converge-based Optimization
Hao Wang, Jingshu Peng, Yanyan Shen +4
Stock recommendation is critical in Fintech applications, which leverage price series and alternative information to estimate future stock performance. Traditional time-series fore…
Automate Strategy Finding with LLM in Quant Investment
Zhizhuo Kou, Holam Yu, Junyu Luo +7
We present a novel three-stage framework leveraging Large Language Models (LLMs) within a risk-aware multi-agent system for automate strategy finding in quantitative finance. Our a…
CARPO: Leveraging Listwise Learning-to-Rank for Context-Aware Query Plan Optimization
Wenrui Zhou, Qiyu Liu, Jingshu Peng +2
Efficient data processing is increasingly vital, with query optimizers playing a fundamental role in translating SQL queries into optimal execution plans. Traditional cost-based op…
Piecewise Linear Approximation in Learned Index Structures: Theoretical and Empirical Analysis
Jiayong Qin, Xianyu Zhu, Qiyu Liu +7
A growing trend in the database and system communities is to augment conventional index structures, such as B+-trees, with machine learning (ML) models. Among these, error-bounded…
Learned Data Compression: Challenges and Opportunities for the Future
Qiyu Liu, Siyuan Han, Jianwei Liao +4
Compressing integer keys is a fundamental operation among multiple communities, such as database management (DB), information retrieval (IR), and high-performance computing (HPC).…