Guardado en:
| Autores principales: | Zhang, Baoming, Chen, MingCai, Song, Jianqing, Li, Shuangjie, Zhang, Jie, Wang, Chongjun |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2501.08581 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Similarity-Navigated Conformal Prediction for Graph Neural Networks
por: Song, Jianqing, et al.
Publicado: (2024)
por: Song, Jianqing, et al.
Publicado: (2024)
Graph Neural Networks with Coarse- and Fine-Grained Division for Mitigating Label Sparsity and Noise
por: Li, Shuangjie, et al.
Publicado: (2024)
por: Li, Shuangjie, et al.
Publicado: (2024)
GaGSL: Global-augmented Graph Structure Learning via Graph Information Bottleneck
por: Li, Shuangjie, et al.
Publicado: (2024)
por: Li, Shuangjie, et al.
Publicado: (2024)
Geometric Imbalance in Semi-Supervised Node Classification
por: Yan, Liang, et al.
Publicado: (2023)
por: Yan, Liang, et al.
Publicado: (2023)
Graph Similarity Regularized Softmax for Semi-Supervised Node Classification
por: Yang, Yiming, et al.
Publicado: (2024)
por: Yang, Yiming, et al.
Publicado: (2024)
Edge-Splitting MLP: Node Classification on Homophilic and Heterophilic Graphs without Message Passing
por: Kohn, Matthias, et al.
Publicado: (2024)
por: Kohn, Matthias, et al.
Publicado: (2024)
Open-World Semi-Supervised Learning for Node Classification
por: Wang, Yanling, et al.
Publicado: (2024)
por: Wang, Yanling, et al.
Publicado: (2024)
CPT: Competence-progressive Training Strategy for Few-shot Node Classification
por: Yan, Qilong, et al.
Publicado: (2024)
por: Yan, Qilong, et al.
Publicado: (2024)
Preference-driven Knowledge Distillation for Few-shot Node Classification
por: Wei, Xing, et al.
Publicado: (2025)
por: Wei, Xing, et al.
Publicado: (2025)
Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition
por: Yan, Liang, et al.
Publicado: (2023)
por: Yan, Liang, et al.
Publicado: (2023)
Non-Homophilic Graph Pre-Training and Prompt Learning
por: Yu, Xingtong, et al.
Publicado: (2024)
por: Yu, Xingtong, et al.
Publicado: (2024)
Semi-Supervised Learning with Multi-Head Co-Training
por: Chen, Mingcai, et al.
Publicado: (2021)
por: Chen, Mingcai, et al.
Publicado: (2021)
Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification
por: Achten, Sonny, et al.
Publicado: (2023)
por: Achten, Sonny, et al.
Publicado: (2023)
Graph-based Semi-supervised Local Clustering with Few Labeled Nodes
por: Shen, Zhaiming, et al.
Publicado: (2022)
por: Shen, Zhaiming, et al.
Publicado: (2022)
Mixed Graph Contrastive Network for Semi-Supervised Node Classification
por: Yang, Xihong, et al.
Publicado: (2022)
por: Yang, Xihong, et al.
Publicado: (2022)
Rethinking Semi-Supervised Node Classification with Self-Supervised Graph Clustering
por: Wang, Songbo, et al.
Publicado: (2025)
por: Wang, Songbo, et al.
Publicado: (2025)
MalMixer: Few-Shot Malware Classification with Retrieval-Augmented Semi-Supervised Learning
por: Li, Jiliang, et al.
Publicado: (2024)
por: Li, Jiliang, et al.
Publicado: (2024)
NodeReg: Mitigating the Imbalance and Distribution Shift Effects in Semi-Supervised Node Classification via Norm Consistency
por: Yang, Shenzhi, et al.
Publicado: (2025)
por: Yang, Shenzhi, et al.
Publicado: (2025)
Semi-Supervised End-To-End Contrastive Learning For Time Series Classification
por: Cai, Huili, et al.
Publicado: (2023)
por: Cai, Huili, et al.
Publicado: (2023)
Hypergraph Contrastive Learning for both Homophilic and Heterophilic Hypergraphs
por: Guan, Renchu, et al.
Publicado: (2025)
por: Guan, Renchu, et al.
Publicado: (2025)
Collaborative Graph Walk for Semi-supervised Multi-Label Node Classification
por: Akujuobi, Uchenna, et al.
Publicado: (2019)
por: Akujuobi, Uchenna, et al.
Publicado: (2019)
Semi-supervised Node Importance Estimation with Informative Distribution Modeling for Uncertainty Regularization
por: Chen, Yankai, et al.
Publicado: (2025)
por: Chen, Yankai, et al.
Publicado: (2025)
Hypergraph Transformer for Semi-Supervised Classification
por: Liu, Zexi, et al.
Publicado: (2023)
por: Liu, Zexi, et al.
Publicado: (2023)
Few-shot Class-incremental Learning for Classification and Object Detection: A Survey
por: Zhang, Jinghua, et al.
Publicado: (2023)
por: Zhang, Jinghua, et al.
Publicado: (2023)
Contrastive Credibility Propagation for Reliable Semi-Supervised Learning
por: Kutt, Brody, et al.
Publicado: (2022)
por: Kutt, Brody, et al.
Publicado: (2022)
Fast Graph Sharpness-Aware Minimization for Enhancing and Accelerating Few-Shot Node Classification
por: Luo, Yihong, et al.
Publicado: (2024)
por: Luo, Yihong, et al.
Publicado: (2024)
Pre-Training and Prompting for Few-Shot Node Classification on Text-Attributed Graphs
por: Zhao, Huanjing, et al.
Publicado: (2024)
por: Zhao, Huanjing, et al.
Publicado: (2024)
E2GNN: Efficient Graph Neural Network Ensembles for Semi-Supervised Classification
por: Zhang, Xin, et al.
Publicado: (2024)
por: Zhang, Xin, et al.
Publicado: (2024)
Neural-Bayesian Program Learning for Few-shot Dialogue Intent Parsing
por: Hong, Mengze, et al.
Publicado: (2024)
por: Hong, Mengze, et al.
Publicado: (2024)
Mixture of Message Passing Experts with Routing Entropy Regularization for Node Classification
por: Chen, Xuanze, et al.
Publicado: (2025)
por: Chen, Xuanze, et al.
Publicado: (2025)
Flatness Improves Backbone Generalisation in Few-shot Classification
por: Li, Rui, et al.
Publicado: (2024)
por: Li, Rui, et al.
Publicado: (2024)
Few-shot Knowledge Graph Relational Reasoning via Subgraph Adaptation
por: Liu, Haochen, et al.
Publicado: (2024)
por: Liu, Haochen, et al.
Publicado: (2024)
Instance Relation Learning Network with Label Knowledge Propagation for Few-shot Multi-label Intent Detection
por: Zhao, Shiman, et al.
Publicado: (2025)
por: Zhao, Shiman, et al.
Publicado: (2025)
Parameter-Free Hypergraph Neural Network for Few-Shot Node Classification
por: Bae, Chaewoon, et al.
Publicado: (2025)
por: Bae, Chaewoon, et al.
Publicado: (2025)
ATLAS: Adaptive Topology-based Learning at Scale for Homophilic and Heterophilic Graphs
por: Kundu, Turja, et al.
Publicado: (2025)
por: Kundu, Turja, et al.
Publicado: (2025)
BoostLLM: Boosting-inspired LLM Fine-tuning for Few-shot Tabular Classification
por: Wang, Yi-Siang, et al.
Publicado: (2026)
por: Wang, Yi-Siang, et al.
Publicado: (2026)
Breaking the Entanglement of Homophily and Heterophily in Semi-supervised Node Classification
por: Sun, Henan, et al.
Publicado: (2023)
por: Sun, Henan, et al.
Publicado: (2023)
Graph Convolutional Network For Semi-supervised Node Classification With Subgraph Sketching
por: Huang, Zibin, et al.
Publicado: (2024)
por: Huang, Zibin, et al.
Publicado: (2024)
(FL)$^2$: Overcoming Few Labels in Federated Semi-Supervised Learning
por: Lee, Seungjoo, et al.
Publicado: (2024)
por: Lee, Seungjoo, et al.
Publicado: (2024)
Summarize-Exemplify-Reflect: Data-driven Insight Distillation Empowers LLMs for Few-shot Tabular Classification
por: Yuan, Yifei, et al.
Publicado: (2025)
por: Yuan, Yifei, et al.
Publicado: (2025)
Ejemplares similares
-
Similarity-Navigated Conformal Prediction for Graph Neural Networks
por: Song, Jianqing, et al.
Publicado: (2024) -
Graph Neural Networks with Coarse- and Fine-Grained Division for Mitigating Label Sparsity and Noise
por: Li, Shuangjie, et al.
Publicado: (2024) -
GaGSL: Global-augmented Graph Structure Learning via Graph Information Bottleneck
por: Li, Shuangjie, et al.
Publicado: (2024) -
Geometric Imbalance in Semi-Supervised Node Classification
por: Yan, Liang, et al.
Publicado: (2023) -
Graph Similarity Regularized Softmax for Semi-Supervised Node Classification
por: Yang, Yiming, et al.
Publicado: (2024)