Cover Image

StructComp: Substituting Propagation with Structural Compression in Training Graph Contrastive Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Shengzhong, Yang, Wenjie, Cao, Xinyuan, Zhang, Hongwei, Huang, Zengfeng
Format:	Preprint
Published:	2023
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Your Graph Recommender is Provably a Single-view Graph Contrastive Learning
by: Yang, Wenjie, et al.
Published: (2024)

Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition
by: Yan, Liang, et al.
Published: (2023)

Load--Reserve Wasserstein Propagation for Isotropic Diffusion Samplers
by: Lyu, Zicheng, et al.
Published: (2026)

Nearly Tight Bounds for Cross-Learning Contextual Bandits with Graphical Feedback
by: Huang, Ruiyuan, et al.
Published: (2025)

High Probability Bound for Cross-Learning Contextual Bandits with Unknown Context Distributions
by: Huang, Ruiyuan, et al.
Published: (2024)

StructPrune: Structured Global Pruning asymptotics with $\mathcal{O}(\sqrt{N})$ GPU Memory
by: Song, Xinyuan, et al.
Published: (2025)

Provable Training for Graph Contrastive Learning
by: Yu, Yue, et al.
Published: (2023)

Geometric Imbalance in Semi-Supervised Node Classification
by: Yan, Liang, et al.
Published: (2023)

Dual-Kernel Graph Community Contrastive Learning
by: Chen, Xiang, et al.
Published: (2025)

Implicit vs Unfolded Graph Neural Networks
by: Yang, Yongyi, et al.
Published: (2021)

RaDAR: Relation-aware Diffusion-Asymmetric Graph Contrastive Learning for Recommendation
by: Huang, Yixuan, et al.
Published: (2026)

CompAct: Compressed Activations for Memory-Efficient LLM Training
by: Shamshoum, Yara, et al.
Published: (2024)

Structure-enhanced Contrastive Learning for Graph Clustering
by: Wu, Xunlian, et al.
Published: (2024)

Re$^2$Math: Benchmarking Theorem Retrieval in Research-Level Mathematics
by: Lyu, Zicheng, et al.
Published: (2026)

FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training
by: Huang, Kezhao, et al.
Published: (2023)

GraphComp: Extreme Error-bounded Compression of Scientific Data via Temporal Graph Autoencoders
by: Li, Guozhong, et al.
Published: (2025)

Graph Structure Refinement with Energy-based Contrastive Learning
by: Zeng, Xianlin, et al.
Published: (2024)

TabStruct: Measuring Structural Fidelity of Tabular Data
by: Jiang, Xiangjian, et al.
Published: (2025)

Rethinking Parameter Sharing as Graph Coloring for Structured Compression
by: Zhang, Boyang, et al.
Published: (2025)

Text2Struct: A Machine Learning Pipeline for Mining Structured Data from Text
by: Zhou, Chaochao, et al.
Published: (2022)

Contrastive Credibility Propagation for Reliable Semi-Supervised Learning
by: Kutt, Brody, et al.
Published: (2022)

Str-GCL: Structural Commonsense Driven Graph Contrastive Learning
by: He, Dongxiao, et al.
Published: (2025)

StructEval: Deepen and Broaden Large Language Model Assessment via Structured Evaluation
by: Cao, Boxi, et al.
Published: (2024)

OmniStruct: Universal Text-to-Structure Generation across Diverse Schemas
by: Huang, James Y., et al.
Published: (2025)

Edge Contrastive Learning: An Augmentation-Free Graph Contrastive Learning Model
by: Li, Yujun, et al.
Published: (2024)

Pre-Training Representations of Binary Code Using Contrastive Learning
by: Zhang, Yifan, et al.
Published: (2022)

Bridging Large Language Models and Graph Structure Learning Models for Robust Representation Learning
by: Su, Guangxin, et al.
Published: (2024)

Rethinking Multi-Label Node Classification: Do Tuned Classic GNNs Suffice?
by: Xiao, Yuxuan, et al.
Published: (2026)

UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation
by: von Rad, Jonathan, et al.
Published: (2026)

StructCoder: Structure-Aware Transformer for Code Generation
by: Tipirneni, Sindhu, et al.
Published: (2022)

Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs
by: Yue, Zichao, et al.
Published: (2025)

StructSynth: Leveraging LLMs for Structure-Aware Tabular Data Synthesis in Low-Data Regimes
by: Liu, Siyi, et al.
Published: (2025)

ID-MixGCL: Identity Mixup for Graph Contrastive Learning
by: Zhang, Gehang, et al.
Published: (2023)

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation
by: Wang, Shuaiqi, et al.
Published: (2025)

StructRL: Recovering Dynamic Programming Structure from Learning Dynamics in Distributional Reinforcement Learning
by: Nowak, Ivo
Published: (2026)

Few Batches or Little Memory, But Not Both: Simultaneous Space and Adaptivity Constraints in Stochastic Bandits
by: Huang, Ruiyuan, et al.
Published: (2026)

RL-Struct: A Lightweight Reinforcement Learning Framework for Reliable Structured Output in LLMs
by: Hu, Ruike, et al.
Published: (2025)

Heterogeneous Graph Contrastive Learning with Spectral Augmentation
by: Zhang, Jing, et al.
Published: (2024)

An Augmentation-Aware Theory for Self-Supervised Contrastive Learning
by: Cui, Jingyi, et al.
Published: (2025)

Why Does Dropping Edges Usually Outperform Adding Edges in Graph Contrastive Learning?
by: Xu, Yanchen, et al.
Published: (2024)