Saved in:
| Main Authors: | Jiang, Wei, Chen, Tong, Ye, Guanhua, Zhang, Wentao, Cui, Lizhen, Huang, Zi, Yin, Hongzhi |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.13605 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
RobGC: Towards Robust Graph Condensation
by: Gao, Xinyi, et al.
Published: (2024)
by: Gao, Xinyi, et al.
Published: (2024)
Memory-enhanced Invariant Prompt Learning for Urban Flow Prediction under Distribution Shifts
by: Jiang, Haiyang, et al.
Published: (2024)
by: Jiang, Haiyang, et al.
Published: (2024)
Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning
by: Gao, Xinyi, et al.
Published: (2024)
by: Gao, Xinyi, et al.
Published: (2024)
Graph Condensation: A Survey
by: Gao, Xinyi, et al.
Published: (2024)
by: Gao, Xinyi, et al.
Published: (2024)
Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition
by: Gao, Xinyi, et al.
Published: (2024)
by: Gao, Xinyi, et al.
Published: (2024)
A Thorough Performance Benchmarking on Lightweight Embedding-based Recommender Systems
by: Tran, Hung Vinh, et al.
Published: (2024)
by: Tran, Hung Vinh, 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)
Progressive Generalization Risk Reduction for Data-Efficient Causal Effect Estimation
by: Wen, Hechuan, et al.
Published: (2024)
by: Wen, Hechuan, et al.
Published: (2024)
On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective
by: Tran, Hung Vinh, et al.
Published: (2024)
by: Tran, Hung Vinh, et al.
Published: (2024)
DFedReweighting: A Unified Framework for Objective-Oriented Reweighting in Decentralized Federated Learning
by: Zhang, Kaichuang, et al.
Published: (2025)
by: Zhang, Kaichuang, et al.
Published: (2025)
Graph Condensation for Open-World Graph Learning
by: Gao, Xinyi, et al.
Published: (2024)
by: Gao, Xinyi, et al.
Published: (2024)
Training-free Heterogeneous Graph Condensation via Data Selection
by: Liang, Yuxuan, et al.
Published: (2024)
by: Liang, Yuxuan, et al.
Published: (2024)
Epidemiology-informed Network for Robust Rumor Detection
by: Jiang, Wei, et al.
Published: (2024)
by: Jiang, Wei, et al.
Published: (2024)
Tackling Data Heterogeneity in Federated Time Series Forecasting
by: Yuan, Wei, et al.
Published: (2024)
by: Yuan, Wei, et al.
Published: (2024)
GraphDLG: Exploring Deep Leakage from Gradients in Federated Graph Learning
by: Wei, Shuyue, et al.
Published: (2026)
by: Wei, Shuyue, et al.
Published: (2026)
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
by: Wen, Hechuan, et al.
Published: (2025)
by: Wen, Hechuan, et al.
Published: (2025)
HGAurban: Heterogeneous Graph Autoencoding for Urban Spatial-Temporal Learning
by: Zhang, Qianru, et al.
Published: (2024)
by: Zhang, Qianru, et al.
Published: (2024)
PUMA: Efficient Continual Graph Learning for Node Classification with Graph Condensation
by: Liu, Yilun, et al.
Published: (2023)
by: Liu, Yilun, et al.
Published: (2023)
LSTM-based Flow Prediction
by: Wang, Hongzhi, et al.
Published: (2019)
by: Wang, Hongzhi, et al.
Published: (2019)
REDUCR: Robust Data Downsampling Using Class Priority Reweighting
by: Bankes, William, et al.
Published: (2023)
by: Bankes, William, et al.
Published: (2023)
IFFair: Influence Function-driven Sample Reweighting for Fair Classification
by: Yang, Jingran, et al.
Published: (2025)
by: Yang, Jingran, et al.
Published: (2025)
On the Limits of Sparse Autoencoders: A Theoretical Framework and Reweighted Remedy
by: Cui, Jingyi, et al.
Published: (2025)
by: Cui, Jingyi, et al.
Published: (2025)
Enhancing Adversarial Training via Reweighting Optimization Trajectory
by: Huang, Tianjin, et al.
Published: (2023)
by: Huang, Tianjin, et al.
Published: (2023)
Residual Reweighted Conformal Prediction for Graph Neural Networks
by: Zhang, Zheng, et al.
Published: (2025)
by: Zhang, Zheng, et al.
Published: (2025)
Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM Generalization
by: Chen, Xuxi, et al.
Published: (2024)
by: Chen, Xuxi, et al.
Published: (2024)
A Comprehensive Survey on Imbalanced Data Learning
by: Gao, Xinyi, et al.
Published: (2025)
by: Gao, Xinyi, et al.
Published: (2025)
An Iteratively Reweighted Method for Sparse Optimization on Nonconvex $\ell_{p}$ Ball
by: Wang, Hao, et al.
Published: (2021)
by: Wang, Hao, et al.
Published: (2021)
Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph
by: Zheng, Weihuang, et al.
Published: (2024)
by: Zheng, Weihuang, et al.
Published: (2024)
Network Distance Based on Laplacian Flows on Graphs
by: Bao, Dianbin, et al.
Published: (2018)
by: Bao, Dianbin, et al.
Published: (2018)
Efficient Content-based Recommendation Model Training via Noise-aware Coreset Selection
by: Tran, Hung Vinh, et al.
Published: (2026)
by: Tran, Hung Vinh, et al.
Published: (2026)
Reweighted Manifold Learning of Collective Variables from Enhanced Sampling Simulations
by: Rydzewski, Jakub, et al.
Published: (2022)
by: Rydzewski, Jakub, et al.
Published: (2022)
How Benchmark Prediction from Fewer Data Misses the Mark
by: Zhang, Guanhua, et al.
Published: (2025)
by: Zhang, Guanhua, et al.
Published: (2025)
ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting
by: Pan, Rui, et al.
Published: (2024)
by: Pan, Rui, et al.
Published: (2024)
Epidemiology-informed Graph Neural Network for Heterogeneity-aware Epidemic Forecasting
by: Zheng, Yufan, et al.
Published: (2024)
by: Zheng, Yufan, et al.
Published: (2024)
Flow Matching is Adaptive to Manifold Structures
by: Kumar, Shivam, et al.
Published: (2026)
by: Kumar, Shivam, et al.
Published: (2026)
Group-robust Sample Reweighting for Subpopulation Shifts via Influence Functions
by: Qiao, Rui, et al.
Published: (2025)
by: Qiao, Rui, et al.
Published: (2025)
TableDART: Dynamic Adaptive Multi-Modal Routing for Table Understanding
by: Xing, Xiaobo, et al.
Published: (2025)
by: Xing, Xiaobo, et al.
Published: (2025)
Hide and Seek in Noise Labels: Noise-Robust Collaborative Active Learning with LLM-Powered Assistance
by: Yuan, Bo, et al.
Published: (2025)
by: Yuan, Bo, et al.
Published: (2025)
STDEN: Towards Physics-Guided Neural Networks for Traffic Flow Prediction
by: Ji, Jiahao, et al.
Published: (2022)
by: Ji, Jiahao, et al.
Published: (2022)
Predicting Large-scale Urban Network Dynamics with Energy-informed Graph Neural Diffusion
by: Nie, Tong, et al.
Published: (2025)
by: Nie, Tong, et al.
Published: (2025)
Similar Items
-
RobGC: Towards Robust Graph Condensation
by: Gao, Xinyi, et al.
Published: (2024) -
Memory-enhanced Invariant Prompt Learning for Urban Flow Prediction under Distribution Shifts
by: Jiang, Haiyang, et al.
Published: (2024) -
Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning
by: Gao, Xinyi, et al.
Published: (2024) -
Graph Condensation: A Survey
by: Gao, Xinyi, et al.
Published: (2024) -
Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition
by: Gao, Xinyi, et al.
Published: (2024)