Copertina

Frequency-aware Graph Signal Processing for Collaborative Filtering

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Xia, Jiafeng, Li, Dongsheng, Gu, Hansu, Lu, Tun, Zhang, Peng, Shang, Li, Gu, Ning
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Information Retrieval Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

GraphTransfer: A Generic Feature Fusion Framework for Collaborative Filtering
di: Xia, Jiafeng, et al.
Pubblicazione: (2024)

Unbiased Collaborative Filtering with Fair Sampling
di: Liu, Jiahao, et al.
Pubblicazione: (2025)

Oracle-guided Dynamic User Preference Modeling for Sequential Recommendation
di: Xia, Jiafeng, et al.
Pubblicazione: (2024)

FedCIA: Federated Collaborative Information Aggregation for Privacy-Preserving Recommendation
di: Han, Mingzhe, et al.
Pubblicazione: (2025)

Transparent and Controllable Recommendation Filtering via Multimodal Multi-Agent Collaboration
di: Zhang, Chi, et al.
Pubblicazione: (2026)

A Comprehensive Summarization and Evaluation of Feature Refinement Modules for CTR Prediction
di: Wang, Fangye, et al.
Pubblicazione: (2023)

AOTree: Aspect Order Tree-based Model for Explainable Recommendation
di: Zhao, Wenxin, et al.
Pubblicazione: (2024)

AgentCF++: Memory-enhanced LLM-based Agents for Popularity-aware Cross-domain Recommendations
di: Liu, Jiahao, et al.
Pubblicazione: (2025)

Feature-Indexed Federated Recommendation with Residual-Quantized Codebooks
di: Han, Mingzhe, et al.
Pubblicazione: (2026)

Filtering Discomforting Recommendations with Large Language Models
di: Liu, Jiahao, et al.
Pubblicazione: (2024)

Drift-Aware Continual Tokenization for Generative Recommendation
di: Feng, Yuebo, et al.
Pubblicazione: (2026)

Improving LLM-powered Recommendations with Personalized Information
di: Liu, Jiahao, et al.
Pubblicazione: (2025)

LLM-Based User Simulation for Low-Knowledge Shilling Attacks on Recommender Systems
di: Gu, Shengkang, et al.
Pubblicazione: (2025)

Graph Signal Diffusion Model for Collaborative Filtering
di: Zhu, Yunqin, et al.
Pubblicazione: (2023)

From Hidden Profiles to Governable Personalization: Recommender Systems in the Age of LLM Agents
di: Liu, Jiahao, et al.
Pubblicazione: (2026)

Bidirectional Knowledge Distillation for Enhancing Sequential Recommendation with Large Language Models
di: Wu, Jiongran, et al.
Pubblicazione: (2025)

Fair Augmentation for Graph Collaborative Filtering
di: Boratto, Ludovico, et al.
Pubblicazione: (2024)

Debiased Collaborative Filtering with Kernel-Based Causal Balancing
di: Li, Haoxuan, et al.
Pubblicazione: (2024)

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

Safe Collaborative Filtering
di: Togashi, Riku, et al.
Pubblicazione: (2023)

Preference and Concurrence Aware Bayesian Graph Neural Networks for Recommender Systems
di: Gu, Hongjian, et al.
Pubblicazione: (2023)

Reconstructing Content via Collaborative Attention to Improve Multimodal Embedding Quality
di: Chen, Jiahan, et al.
Pubblicazione: (2026)

TFPS: A Temporal Filtration-enhanced Positive Sample Set Construction Method for Implicit Collaborative Filtering
di: Wu, Jiayi, et al.
Pubblicazione: (2026)

Learning to Fast Unrank in Collaborative Filtering Recommendation
di: Zhao, Junpeng, et al.
Pubblicazione: (2025)

How Does Message Passing Improve Collaborative Filtering?
di: Ju, Mingxuan, et al.
Pubblicazione: (2024)

An Evaluation Study of Generative Adversarial Networks for Collaborative Filtering
di: Maurera, Fernando Benjamín Pérez, et al.
Pubblicazione: (2022)

ImplicitSLIM and How it Improves Embedding-based Collaborative Filtering
di: Shenbin, Ilya, et al.
Pubblicazione: (2024)

Vectorized Context-Aware Embeddings for GAT-Based Collaborative Filtering
di: Ebrat, Danial, et al.
Pubblicazione: (2025)

Broad Recommender System: An Efficient Nonlinear Collaborative Filtering Approach
di: Huang, Ling, et al.
Pubblicazione: (2022)

On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective
di: Loveland, Donald, et al.
Pubblicazione: (2025)

Collaborative Filtering Through Weighted Similarities of User and Item Embeddings
di: Pires, Pedro R., et al.
Pubblicazione: (2026)

Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach
di: Li, Zhiwei, et al.
Pubblicazione: (2024)

Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution
di: Xu, Cong, et al.
Pubblicazione: (2023)

Text-Driven Neural Collaborative Filtering Model for Paper Source Tracing
di: Xu, Aobo, et al.
Pubblicazione: (2024)

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

Graph Spectral Filtering with Chebyshev Interpolation for Recommendation
di: Kim, Chanwoo, et al.
Pubblicazione: (2025)

Revealing and Utilizing In-group Favoritism for Graph-based Collaborative Filtering
di: Jung, Hoin, et al.
Pubblicazione: (2024)

PolyCF: Towards the Optimal Spectral Graph Filters for Collaborative Filtering
di: Qin, Yifang, et al.
Pubblicazione: (2024)

Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential Recommendation
di: Wei, Shaowei, et al.
Pubblicazione: (2024)

Debiasing Message Passing to Mitigate Popularity Bias in GNN-based Collaborative Filtering
di: Islam, Md Aminul, et al.
Pubblicazione: (2026)