ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2404.12008
  4. Cited By
How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective
v1v2v3v4v5 (latest)

How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective

18 April 2024
Siyi Lin
Chongming Gao
Jiawei Chen
Sheng Zhou
Binbin Hu
Yan Feng
Chun-Yen Chen
Can Wang
ArXiv (abs)PDFHTML

Papers citing "How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective"

27 / 27 papers shown
Title
Taming Recommendation Bias with Causal Intervention on Evolving Personal Popularity
Taming Recommendation Bias with Causal Intervention on Evolving Personal Popularity
Shiyin Tan
Dongyuan Li
Renhe Jiang
Zhen Wang
Xingtong Yu
Manabu Okumura
CML
153
0
0
20 May 2025
On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective
On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective
Donald Loveland
Mingxuan Ju
Tong Zhao
Neil Shah
Danai Koutra
77
0
0
16 May 2025
TransDiffuser: End-to-end Trajectory Generation with Decorrelated Multi-modal Representation for Autonomous Driving
TransDiffuser: End-to-end Trajectory Generation with Decorrelated Multi-modal Representation for Autonomous Driving
Xuefeng Jiang
Yuan Ma
Pengxiang Li
Leimeng Xu
Xin Wen
Kun Zhan
Zhongpu Xia
Peng Jia
Xianpeng Lang
Sheng Sun
DiffM
72
1
0
14 May 2025
Test Time Embedding Normalization for Popularity Bias Mitigation
Test Time Embedding Normalization for Popularity Bias Mitigation
Dain Kim
Jinhyeok Park
Dongwoo Kim
40
8
0
22 Aug 2023
Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased
  Recommendations
Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations
Haoxuan Li
Yanghao Xiao
Chunyuan Zheng
Peng Wu
CML
80
51
0
17 Apr 2023
Adap-$τ$: Adaptively Modulating Embedding Magnitude for
  Recommendation
Adap-τττ: Adaptively Modulating Embedding Magnitude for Recommendation
Jiawei Chen
Junkang Wu
Jiancan Wu
Sheng Zhou
Xuezhi Cao
Xiangnan He
86
33
0
09 Feb 2023
Debiased Recommendation with Neural Stratification
Debiased Recommendation with Neural Stratification
Quanyu Dai
Zhenhua Dong
Xu Chen
74
4
0
15 Aug 2022
ResNorm: Tackling Long-tailed Degree Distribution Issue in Graph Neural
  Networks via Normalization
ResNorm: Tackling Long-tailed Degree Distribution Issue in Graph Neural Networks via Normalization
Langzhang Liang
Zenglin Xu
Zixing Song
Irwin King
Yuan Qi
Jieping Ye
102
22
0
16 Jun 2022
Improving Graph Collaborative Filtering with Neighborhood-enriched
  Contrastive Learning
Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning
Zihan Lin
Changxin Tian
Yupeng Hou
Wayne Xin Zhao
64
434
0
13 Feb 2022
AutoDebias: Learning to Debias for Recommendation
AutoDebias: Learning to Debias for Recommendation
Jiawei Chen
Hande Dong
Yang Qiu
Xiangnan He
Xin Xin
Liang Chen
Guli Lin
Keping Yang
CML
116
205
0
10 May 2021
A Survey on Accuracy-oriented Neural Recommendation: From Collaborative
  Filtering to Information-rich Recommendation
A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation
Le Wu
Xiangnan He
Xiang Wang
Kun Zhang
Meng Wang
HAI
74
296
0
27 Apr 2021
Item Recommendation from Implicit Feedback
Item Recommendation from Implicit Feedback
Steffen Rendle
98
43
0
21 Jan 2021
Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit
  Bias towards Low Rank
Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit Bias towards Low Rank
H. Chou
Carsten Gieshoff
J. Maly
Holger Rauhut
52
42
0
27 Nov 2020
Self-supervised Graph Learning for Recommendation
Self-supervised Graph Learning for Recommendation
Jiancan Wu
Xiang Wang
Fuli Feng
Xiangnan He
Liang Chen
Jianxun Lian
Xing Xie
SSL
174
1,163
0
21 Oct 2020
Long-Tailed Classification by Keeping the Good and Removing the Bad
  Momentum Causal Effect
Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect
Kaihua Tang
Jianqiang Huang
Hanwang Zhang
CML
101
446
0
28 Sep 2020
Graph Convolutional Network for Recommendation with Low-pass
  Collaborative Filters
Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters
Wenhui Yu
Zheng Qin
GNN
55
94
0
28 Jun 2020
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
Implicit Regularization in Deep Matrix Factorization
Implicit Regularization in Deep Matrix Factorization
Sanjeev Arora
Nadav Cohen
Wei Hu
Yuping Luo
AI4CE
85
509
0
31 May 2019
A mathematical theory of semantic development in deep neural networks
A mathematical theory of semantic development in deep neural networks
Andrew M. Saxe
James L. McClelland
Surya Ganguli
73
271
0
23 Oct 2018
News Session-Based Recommendations using Deep Neural Networks
News Session-Based Recommendations using Deep Neural Networks
Gabriel de Souza P. Moreira
F. Ferreira
A. Cunha
50
81
0
31 Jul 2018
DeepInf: Social Influence Prediction with Deep Learning
DeepInf: Social Influence Prediction with Deep Learning
J. Qiu
Jian Tang
Hao Ma
Yuxiao Dong
Kuansan Wang
Jie Tang
GNNAI4CE
79
545
0
15 Jul 2018
Deep Interest Network for Click-Through Rate Prediction
Deep Interest Network for Click-Through Rate Prediction
Guorui Zhou
Cheng-Ning Song
Xiaoqiang Zhu
Xi-Wang Dai
Ziru Xu
Xiao Ma
Yanghui Yan
Junqi Jin
Han Li
Kun Gai
76
1,823
0
21 Jun 2017
Spectral Norm Regularization for Improving the Generalizability of Deep
  Learning
Spectral Norm Regularization for Improving the Generalizability of Deep Learning
Yuichi Yoshida
Takeru Miyato
81
334
0
31 May 2017
TensorFlow: A system for large-scale machine learning
TensorFlow: A system for large-scale machine learning
Martín Abadi
P. Barham
Jianmin Chen
Zhiwen Chen
Andy Davis
...
Vijay Vasudevan
Pete Warden
Martin Wicke
Yuan Yu
Xiaoqiang Zhang
GNNAI4CE
433
18,361
0
27 May 2016
Recommendations as Treatments: Debiasing Learning and Evaluation
Recommendations as Treatments: Debiasing Learning and Evaluation
Tobias Schnabel
Adith Swaminathan
Ashudeep Singh
Navin Chandak
Thorsten Joachims
CML
162
686
0
17 Feb 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.0K
150,260
0
22 Dec 2014
BPR: Bayesian Personalized Ranking from Implicit Feedback
BPR: Bayesian Personalized Ranking from Implicit Feedback
Steffen Rendle
Christoph Freudenthaler
Zeno Gantner
Lars Schmidt-Thieme
BDL
152
5,734
0
09 May 2012
1