Cover Image

Multi-Channel Hypergraph Contrastive Learning for Matrix Completion

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Xiang, Shui, Changsheng, Zhao, Zhongying, Dong, Junyu, Yu, Yanwei
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Information Retrieval
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Dual-Channel Multiplex Graph Neural Networks for Recommendation
by: Li, Xiang, et al.
Published: (2024)

Lightweight yet Fine-grained: A Graph Capsule Convolutional Network with Subspace Alignment for Shared-account Sequential Recommendation
by: Zhang, Jinyu, et al.
Published: (2024)

Knowledge-Aware Multi-Intent Contrastive Learning for Multi-Behavior Recommendation
by: Liang, Shunpan, et al.
Published: (2024)

Lightweight yet Efficient: An External Attentive Graph Convolutional Network with Positional Prompts for Sequential Recommendation
by: Zhang, Jinyu, et al.
Published: (2025)

In-context Contrastive Learning for Event Causality Identification
by: Liang, Chao, et al.
Published: (2024)

Dual-Channel Latent Factor Analysis Enhanced Graph Contrastive Learning for Recommendation
by: Long, Junfeng, et al.
Published: (2024)

Online Matrix Completion: A Collaborative Approach with Hott Items
by: Baby, Dheeraj, et al.
Published: (2024)

Against Filter Bubbles: Diversified Music Recommendation via Weighted Hypergraph Embedding Learning
by: Luo, Chaoguang, et al.
Published: (2024)

From Graphs to Hypergraphs: Hypergraph Projection and its Remediation
by: Wang, Yanbang, et al.
Published: (2024)

Mixed Supervised Graph Contrastive Learning for Recommendation
by: Zhang, Weizhi, et al.
Published: (2024)

Contrastive Learning for Cold Start Recommendation with Adaptive Feature Fusion
by: Hu, Jiacheng, et al.
Published: (2025)

ID and Graph View Contrastive Learning with Multi-View Attention Fusion for Sequential Recommendation
by: Zhou, Xiaofan, et al.
Published: (2026)

Multi-view Attention Fusion of Heterogeneous Hypergraph with Dynamic Behavioral Profiling for Personalized Learning Resource Recommendation
by: Xie, Tao, et al.
Published: (2026)

L^2CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative Filtering
by: Jin, Xinzhou, et al.
Published: (2024)

Enhancing Interpretability and Effectiveness in Recommendation with Numerical Features via Learning to Contrast the Counterfactual samples
by: Xu, Xiaoxiao, et al.
Published: (2025)

MFRS: A Multi-Frequency Reference Series Approach to Scalable and Accurate Time-Series Forecasting
by: Yu, Liang, et al.
Published: (2025)

Contrastive Learning for Diversity-Aware Product Recommendations in Retail
by: Karlis, Vasileios, et al.
Published: (2026)

Generative-Contrastive Heterogeneous Graph Neural Network
by: Wang, Yu, et al.
Published: (2024)

DisCo: Graph-Based Disentangled Contrastive Learning for Cold-Start Cross-Domain Recommendation
by: Li, Hourun, et al.
Published: (2024)

GraphFusionSBR: Denoising Multi-Channel Graphs for Session-Based Recommendation
by: He, Jia-Xin, et al.
Published: (2026)

Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank
by: Loveland, Donald, et al.
Published: (2024)

DeepMTL2R: A Library for Deep Multi-task Learning to Rank
by: Dong, Chaosheng, et al.
Published: (2026)

Graph Contrastive Learning for Optimizing Sparse Data in Recommender Systems with LightGCL
by: Jatavallabha, Aravinda, et al.
Published: (2025)

Symmetric Graph Contrastive Learning against Noisy Views for Recommendation
by: Zhao, Chu, et al.
Published: (2024)

Estimating the Hessian Matrix of Ranking Objectives for Stochastic Learning to Rank with Gradient Boosted Trees
by: Kang, Jingwei, et al.
Published: (2024)

Exploring Contrastive Learning for Long-Tailed Multi-Label Text Classification
by: Audibert, Alexandre, et al.
Published: (2024)

MODRL-TA:A Multi-Objective Deep Reinforcement Learning Framework for Traffic Allocation in E-Commerce Search
by: Cheng, Peng, et al.
Published: (2024)

Multi-task Offline Reinforcement Learning for Online Advertising in Recommender Systems
by: Liu, Langming, et al.
Published: (2025)

Retrievable Domain-Sensitive Feature Memory for Multi-Domain Recommendation
by: Zhao, Yuang, et al.
Published: (2024)

FewUser: Few-Shot Social User Geolocation via Contrastive Learning
by: Li, Menglin, et al.
Published: (2024)

Enhancing Travel Decision-Making: A Contrastive Learning Approach for Personalized Review Rankings in Accommodations
by: Igebaria, Reda, et al.
Published: (2024)

SLSREC: Self-Supervised Contrastive Learning for Adaptive Fusion of Long- and Short-Term User Interests
by: Zhou, Wei, et al.
Published: (2026)

FedHCDR: Federated Cross-Domain Recommendation with Hypergraph Signal Decoupling
by: Zhang, Hongyu, et al.
Published: (2024)

Adaptive Conditional Expert Selection Network for Multi-domain Recommendation
by: Dong, Kuiyao, et al.
Published: (2024)

See Beyond a Single View: Multi-Attribution Learning Leads to Better Conversion Rate Prediction
by: Chen, Sishuo, et al.
Published: (2025)

Research on Short-Video Platform User Decision-Making via Multimodal Temporal Modeling and Reinforcement Learning
by: Wang, Jinmeiyang, et al.
Published: (2025)

EnhancedRL: An Enhanced-State Reinforcement Learning Algorithm for Multi-Task Fusion in Recommender Systems
by: Liu, Peng, et al.
Published: (2024)

Accelerating Matrix Factorization by Dynamic Pruning for Fast Recommendation
by: Wu, Yining, et al.
Published: (2024)

Does Weighting Improve Matrix Factorization for Recommender Systems?
by: Ayoub, Alex, et al.
Published: (2025)

Search Intenion Network for Personalized Query Auto-Completion in E-Commerce
by: Bao, Wei, et al.
Published: (2024)