Graph-Based Feature Augmentation for Predictive Tasks on Relational Datasets
Fuente:
arXiv
Saved in:
| Main Authors: | Qiao, Lianpeng, Cao, Ziqi, Feng, Kaiyu, Yuan, Ye, Wang, Guoren |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Hippasus: Effective and Efficient Automatic Feature Augmentation for Machine Learning Tasks on Relational Data
by: Papadias, Serafeim, et al.
Published: (2026)
by: Papadias, Serafeim, et al.
Published: (2026)
Theoretically and Practically Efficient Resistance Distance Computation on Large Graphs
by: Yang, Yichun, et al.
Published: (2026)
by: Yang, Yichun, et al.
Published: (2026)
Graph Learning in the Era of LLMs: A Survey from the Perspective of Data, Models, and Tasks
by: Li, Xunkai, et al.
Published: (2024)
by: Li, Xunkai, et al.
Published: (2024)
Gaussian Relational Graph Transformer
by: Ding, Zezhong, et al.
Published: (2026)
by: Ding, Zezhong, et al.
Published: (2026)
4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on Relational DBs
by: Wang, Minjie, et al.
Published: (2024)
by: Wang, Minjie, et al.
Published: (2024)
Graph Structure Learning for Spatial-Temporal Imputation: Adapting to Node and Feature Scales
by: Yang, Xinyu, et al.
Published: (2024)
by: Yang, Xinyu, et al.
Published: (2024)
FeatAug: Automatic Feature Augmentation From One-to-Many Relationship Tables
by: Qi, Danrui, et al.
Published: (2024)
by: Qi, Danrui, et al.
Published: (2024)
SchemaDB: Structures in Relational Datasets
by: Christopher, Cody James, et al.
Published: (2021)
by: Christopher, Cody James, et al.
Published: (2021)
FeatNavigator: Automatic Feature Augmentation on Tabular Data
by: Liang, Jiaming, et al.
Published: (2024)
by: Liang, Jiaming, et al.
Published: (2024)
Task-Agnostic Contrastive Pretraining for Relational Deep Learning
by: Peleška, Jakub, et al.
Published: (2025)
by: Peleška, Jakub, et al.
Published: (2025)
Graph-Structured Data Analysis of Component Failure in Autonomous Cargo Ships Based on Feature Fusion
by: Zhang, Zizhao, et al.
Published: (2025)
by: Zhang, Zizhao, et al.
Published: (2025)
Efficient Exact Resistance Distance Computation on Small-Treewidth Graphs: a Labelling Approach
by: Liao, Meihao, et al.
Published: (2025)
by: Liao, Meihao, et al.
Published: (2025)
StreamTGN: A GPU-Efficient Serving System for Streaming Temporal Graph Neural Networks
by: Zhang, Lingling, et al.
Published: (2026)
by: Zhang, Lingling, et al.
Published: (2026)
Retrieve, Merge, Predict: Augmenting Tables with Data Lakes
by: Cappuzzo, Riccardo, et al.
Published: (2024)
by: Cappuzzo, Riccardo, et al.
Published: (2024)
Learning-based Sketches for Frequency Estimation in Data Streams without Ground Truth
by: Yuan, Xinyu, et al.
Published: (2024)
by: Yuan, Xinyu, et al.
Published: (2024)
Federated Prototype Graph Learning
by: Wu, Zhengyu, et al.
Published: (2025)
by: Wu, Zhengyu, et al.
Published: (2025)
Learned Graph Rewriting with Equality Saturation: A New Paradigm in Relational Query Rewrite and Beyond
by: Bărbulescu, George-Octavian, et al.
Published: (2024)
by: Bărbulescu, George-Octavian, et al.
Published: (2024)
Synthesize, Retrieve, and Propagate: A Unified Predictive Modeling Framework for Relational Databases
by: Li, Ning, et al.
Published: (2025)
by: Li, Ning, et al.
Published: (2025)
Predictive Query-based Pipeline for Graph Data
by: Neto, Plácido A Souza
Published: (2024)
by: Neto, Plácido A Souza
Published: (2024)
Bi-Directional Multi-Scale Graph Dataset Condensation via Information Bottleneck
by: Fu, Xingcheng, et al.
Published: (2024)
by: Fu, Xingcheng, et al.
Published: (2024)
Numerical Literals in Link Prediction: A Critical Examination of Models and Datasets
by: Blum, Moritz, et al.
Published: (2024)
by: Blum, Moritz, et al.
Published: (2024)
Relational Database Distillation: From Structured Tables to Condensed Graph Data
by: Gao, Xinyi, et al.
Published: (2025)
by: Gao, Xinyi, et al.
Published: (2025)
FedGTA: Topology-aware Averaging for Federated Graph Learning
by: Li, Xunkai, et al.
Published: (2024)
by: Li, Xunkai, et al.
Published: (2024)
Relational Graph Transformer
by: Dwivedi, Vijay Prakash, et al.
Published: (2025)
by: Dwivedi, Vijay Prakash, et al.
Published: (2025)
Towards Data-centric Machine Learning on Directed Graphs: a Survey
by: Sun, Henan, et al.
Published: (2024)
by: Sun, Henan, et al.
Published: (2024)
Toward Scalable Graph Unlearning: A Node Influence Maximization based Approach
by: Li, Xunkai, et al.
Published: (2025)
by: Li, Xunkai, et al.
Published: (2025)
Pruning Minimal Reasoning Graphs for Efficient Retrieval-Augmented Generation
by: Wang, Ning, et al.
Published: (2026)
by: Wang, Ning, et al.
Published: (2026)
The Hybrid Multimodal Graph Index (HMGI): A Comprehensive Framework for Integrated Relational and Vector Search
by: Chandra, Joydeep, et al.
Published: (2025)
by: Chandra, Joydeep, et al.
Published: (2025)
Griffin: Towards a Graph-Centric Relational Database Foundation Model
by: Wang, Yanbo, et al.
Published: (2025)
by: Wang, Yanbo, et al.
Published: (2025)
Toward Data-centric Directed Graph Learning: An Entropy-driven Approach
by: Li, Xunkai, et al.
Published: (2025)
by: Li, Xunkai, et al.
Published: (2025)
DATA-WA: Demand-based Adaptive Task Assignment with Dynamic Worker Availability Windows
by: Chen, Jinwen, et al.
Published: (2025)
by: Chen, Jinwen, et al.
Published: (2025)
RDBLearn: Simple In-Context Prediction Over Relational Databases
by: Zhang, Yanlin, et al.
Published: (2026)
by: Zhang, Yanlin, et al.
Published: (2026)
Contributing Dimension Structure of Deep Feature for Coreset Selection
by: Wan, Zhijing, et al.
Published: (2024)
by: Wan, Zhijing, et al.
Published: (2024)
MICRO: A Lightweight Middleware for Optimizing Cross-store Cross-model Graph-Relation Joins [Technical Report]
by: Zheng, Xiuwen, et al.
Published: (2026)
by: Zheng, Xiuwen, et al.
Published: (2026)
OpenGLT: A Comprehensive Benchmark of Graph Neural Networks for Graph-Level Tasks
by: Li, Haoyang, et al.
Published: (2025)
by: Li, Haoyang, et al.
Published: (2025)
Pre-Execution Query Slot-Time Prediction in Cloud Data Warehouses: A Feature-Scoped Machine Learning Approach
by: Pathak, Prashant Kumar
Published: (2026)
by: Pathak, Prashant Kumar
Published: (2026)
Optimizing LLM Queries in Relational Data Analytics Workloads
by: Liu, Shu, et al.
Published: (2024)
by: Liu, Shu, et al.
Published: (2024)
HHGT: Hierarchical Heterogeneous Graph Transformer for Heterogeneous Graph Representation Learning
by: Zhu, Qiuyu, et al.
Published: (2024)
by: Zhu, Qiuyu, et al.
Published: (2024)
Towards Pattern-aware Data Augmentation for Temporal Knowledge Graph Completion
by: Zhang, Jiasheng, et al.
Published: (2024)
by: Zhang, Jiasheng, et al.
Published: (2024)
Towards Unbiased Federated Graph Learning: Label and Topology Perspectives
by: Wu, Zhengyu, et al.
Published: (2025)
by: Wu, Zhengyu, et al.
Published: (2025)
Similar Items
-
Hippasus: Effective and Efficient Automatic Feature Augmentation for Machine Learning Tasks on Relational Data
by: Papadias, Serafeim, et al.
Published: (2026) -
Theoretically and Practically Efficient Resistance Distance Computation on Large Graphs
by: Yang, Yichun, et al.
Published: (2026) -
Graph Learning in the Era of LLMs: A Survey from the Perspective of Data, Models, and Tasks
by: Li, Xunkai, et al.
Published: (2024) -
Gaussian Relational Graph Transformer
by: Ding, Zezhong, et al.
Published: (2026) -
4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on Relational DBs
by: Wang, Minjie, et al.
Published: (2024)