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When SparseMoE Meets Noisy Interactions: An Ensemble View on Denoising Recommendation

When SparseMoE Meets Noisy Interactions: An Ensemble View on Denoising Recommendation

Weipu Chen
Zhuangzhuang He
Fei Liu
ArXiv (abs)PDFHTMLGithub (1★)

Papers citing "When SparseMoE Meets Noisy Interactions: An Ensemble View on Denoising Recommendation"

7 / 7 papers shown
Title
Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering
Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering
Peijie Sun
Le Wu
Kun Zhang
Xiangzhi Chen
Mengdi Wang
51
21
0
18 Feb 2024
Efficient Bi-Level Optimization for Recommendation Denoising
Efficient Bi-Level Optimization for Recommendation Denoising
Zongwei Wang
Min Gao
Wentao Li
Junliang Yu
Linxin Guo
Hongzhi Yin
69
31
0
19 Oct 2022
Evolutionary bagging for ensemble learning
Evolutionary bagging for ensemble learning
Giang Ngo
R. Beard
Rohitash Chandra
BDL
66
119
0
04 Aug 2022
LightFR: Lightweight Federated Recommendation with Privacy-preserving Matrix Factorization
LightFR: Lightweight Federated Recommendation with Privacy-preserving Matrix Factorization
Honglei Zhang
Fangyuan Luo
Jun Wu
Xiangnan He
Yidong Li
67
82
0
23 Jun 2022
Learning Robust Recommenders through Cross-Model Agreement
Learning Robust Recommenders through Cross-Model Agreement
Yu Wang
Xin Xin
Zaiqiao Meng
Xiangnan He
J. Jose
Fuli Feng
61
51
0
20 May 2021
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
Xiangnan He
Kuan Deng
Xiang Wang
Yan Li
Yongdong Zhang
Meng Wang
GNN
189
3,671
0
06 Feb 2020
XGBoost: A Scalable Tree Boosting System
XGBoost: A Scalable Tree Boosting System
Tianqi Chen
Carlos Guestrin
809
38,961
0
09 Mar 2016