Relational Database Distillation: From Structured Tables to Condensed Graph Data
Fuente:
arXiv
Guardado en:
| Autores principales: | Gao, Xinyi, Zhang, Jingxi, Chen, Lijian, Chen, Tong, Cui, Lizhen, Yin, Hongzhi |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
RobGC: Towards Robust Graph Condensation
por: Gao, Xinyi, et al.
Publicado: (2024)
por: Gao, Xinyi, et al.
Publicado: (2024)
Graph Condensation for Open-World Graph Learning
por: Gao, Xinyi, et al.
Publicado: (2024)
por: Gao, Xinyi, et al.
Publicado: (2024)
Training-free Heterogeneous Graph Condensation via Data Selection
por: Liang, Yuxuan, et al.
Publicado: (2024)
por: Liang, Yuxuan, et al.
Publicado: (2024)
Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning
por: Gao, Xinyi, et al.
Publicado: (2024)
por: Gao, Xinyi, et al.
Publicado: (2024)
Graph Condensation: A Survey
por: Gao, Xinyi, et al.
Publicado: (2024)
por: Gao, Xinyi, et al.
Publicado: (2024)
Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition
por: Gao, Xinyi, et al.
Publicado: (2024)
por: Gao, Xinyi, et al.
Publicado: (2024)
Graph Neural Networks on Graph Databases
por: Lopushanskyy, Dmytro, et al.
Publicado: (2024)
por: Lopushanskyy, Dmytro, et al.
Publicado: (2024)
Bi-Directional Multi-Scale Graph Dataset Condensation via Information Bottleneck
por: Fu, Xingcheng, et al.
Publicado: (2024)
por: Fu, Xingcheng, et al.
Publicado: (2024)
Rel-MOSS: Towards Imbalanced Relational Deep Learning on Relational Databases
por: Yin, Jun, et al.
Publicado: (2026)
por: Yin, Jun, et al.
Publicado: (2026)
Griffin: Towards a Graph-Centric Relational Database Foundation Model
por: Wang, Yanbo, et al.
Publicado: (2025)
por: Wang, Yanbo, et al.
Publicado: (2025)
In-Database Data Imputation
por: Perini, Massimo, et al.
Publicado: (2024)
por: Perini, Massimo, et al.
Publicado: (2024)
Database Views as Explanations for Relational Deep Learning
por: Rissaki, Agapi, et al.
Publicado: (2025)
por: Rissaki, Agapi, et al.
Publicado: (2025)
Differentially Private Synthetic Data Generation for Relational Databases
por: Alimohammadi, Kaveh, et al.
Publicado: (2024)
por: Alimohammadi, Kaveh, et al.
Publicado: (2024)
IRG: Modular Synthetic Relational Database Generation with Complex Relational Schemas
por: Li, Jiayu, et al.
Publicado: (2023)
por: Li, Jiayu, et al.
Publicado: (2023)
Synthesize, Retrieve, and Propagate: A Unified Predictive Modeling Framework for Relational Databases
por: Li, Ning, et al.
Publicado: (2025)
por: Li, Ning, et al.
Publicado: (2025)
Iterative Forgetting: Online Data Stream Regression Using Database-Inspired Adaptive Granulation
por: Kathiriya, Niket, et al.
Publicado: (2024)
por: Kathiriya, Niket, et al.
Publicado: (2024)
Top Ten Challenges Towards Agentic Neural Graph Databases
por: Bai, Jiaxin, et al.
Publicado: (2025)
por: Bai, Jiaxin, et al.
Publicado: (2025)
Trading Vector Data in Vector Databases
por: Cheng, Jin, et al.
Publicado: (2025)
por: Cheng, Jin, et al.
Publicado: (2025)
CardBench: A Benchmark for Learned Cardinality Estimation in Relational Databases
por: Chronis, Yannis, et al.
Publicado: (2024)
por: Chronis, Yannis, et al.
Publicado: (2024)
FedST: Secure Federated Shapelet Transformation for Time Series Classification
por: Liang, Zhiyu, et al.
Publicado: (2023)
por: Liang, Zhiyu, et al.
Publicado: (2023)
Graph2Region: Efficient Graph Similarity Learning with Structure and Scale Restoration
por: Liu, Zhouyang, et al.
Publicado: (2025)
por: Liu, Zhouyang, et al.
Publicado: (2025)
Rethinking Federated Graph Learning: A Data Condensation Perspective
por: Zhang, Hao, et al.
Publicado: (2025)
por: Zhang, Hao, et al.
Publicado: (2025)
Graph Structure Learning for Spatial-Temporal Imputation: Adapting to Node and Feature Scales
por: Yang, Xinyu, et al.
Publicado: (2024)
por: Yang, Xinyu, et al.
Publicado: (2024)
RDBLearn: Simple In-Context Prediction Over Relational Databases
por: Zhang, Yanlin, et al.
Publicado: (2026)
por: Zhang, Yanlin, et al.
Publicado: (2026)
L2T-Tune:LLM-Guided Hybrid Database Tuning with LHS and TD3
por: Yang, Xinyue, et al.
Publicado: (2025)
por: Yang, Xinyue, et al.
Publicado: (2025)
TimeCSL: Unsupervised Contrastive Learning of General Shapelets for Explorable Time Series Analysis
por: Liang, Zhiyu, et al.
Publicado: (2024)
por: Liang, Zhiyu, et al.
Publicado: (2024)
UniTS: A Universal Time Series Analysis Framework Powered by Self-Supervised Representation Learning
por: Liang, Zhiyu, et al.
Publicado: (2023)
por: Liang, Zhiyu, et al.
Publicado: (2023)
C$^{2}$TC: A Training-Free Framework for Efficient Tabular Data Condensation
por: Xu, Sijia, et al.
Publicado: (2026)
por: Xu, Sijia, et al.
Publicado: (2026)
Graph-Structured Data Analysis of Component Failure in Autonomous Cargo Ships Based on Feature Fusion
por: Zhang, Zizhao, et al.
Publicado: (2025)
por: Zhang, Zizhao, et al.
Publicado: (2025)
Privacy-Preserved Neural Graph Databases
por: Hu, Qi, et al.
Publicado: (2023)
por: Hu, Qi, et al.
Publicado: (2023)
Gaussian Relational Graph Transformer
por: Ding, Zezhong, et al.
Publicado: (2026)
por: Ding, Zezhong, et al.
Publicado: (2026)
Exploring the Heterogeneity of Tabular Data: A Diversity-aware Data Generator via LLMs
por: Tang, Yafeng, et al.
Publicado: (2025)
por: Tang, Yafeng, et al.
Publicado: (2025)
RelBench: A Benchmark for Deep Learning on Relational Databases
por: Robinson, Joshua, et al.
Publicado: (2024)
por: Robinson, Joshua, et al.
Publicado: (2024)
HAKES: Scalable Vector Database for Embedding Search Service
por: Hu, Guoyu, et al.
Publicado: (2025)
por: Hu, Guoyu, et al.
Publicado: (2025)
View-based Explanations for Graph Neural Networks
por: Chen, Tingyang, et al.
Publicado: (2024)
por: Chen, Tingyang, et al.
Publicado: (2024)
Towards Practical Benchmarking of Data Cleaning Techniques: On Generating Authentic Errors via Large Language Models
por: Liu, Xinyuan, et al.
Publicado: (2025)
por: Liu, Xinyuan, et al.
Publicado: (2025)
Auto-Test: Learning Semantic-Domain Constraints for Unsupervised Error Detection in Tables
por: Chen, Qixu, et al.
Publicado: (2025)
por: Chen, Qixu, et al.
Publicado: (2025)
SchemaDB: Structures in Relational Datasets
por: Christopher, Cody James, et al.
Publicado: (2021)
por: Christopher, Cody James, et al.
Publicado: (2021)
Observatory: Characterizing Embeddings of Relational Tables
por: Cong, Tianji, et al.
Publicado: (2023)
por: Cong, Tianji, et al.
Publicado: (2023)
WikiDBGraph: A Data Management Benchmark Suite for Collaborative Learning over Database Silos
por: Wu, Zhaomin, et al.
Publicado: (2025)
por: Wu, Zhaomin, et al.
Publicado: (2025)
Ejemplares similares
-
RobGC: Towards Robust Graph Condensation
por: Gao, Xinyi, et al.
Publicado: (2024) -
Graph Condensation for Open-World Graph Learning
por: Gao, Xinyi, et al.
Publicado: (2024) -
Training-free Heterogeneous Graph Condensation via Data Selection
por: Liang, Yuxuan, et al.
Publicado: (2024) -
Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning
por: Gao, Xinyi, et al.
Publicado: (2024) -
Graph Condensation: A Survey
por: Gao, Xinyi, et al.
Publicado: (2024)