Fetching the paper…
Reading the bibliography…
Multimedia-based recommendation provides personalized item suggestions by learning the content preferences of users.
BPR: Bayesian Personalized Ranking from Implicit Feedback
Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009 · 2009
Earlier work this paper cites.
Deep content-based music recommendation
Aäron van den Oord, Sander Dieleman, and Benjamin Schrauwen. 2013 · 2013
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
Diederik P. Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
Social collaborative filtering for cold-start recommendations
Suvash Sedhain, Scott Sanner, Darius Braziunas, Lexing Xie, and Jordan Christensen. 2014 · 2014
Earlier work this paper cites.
Learning image and user features for recommendation in social networks
Xue Geng, Hanwang Zhang, Jingwen Bian, and Tat-Seng Chua. 2015 · 2015
Earlier work this paper cites.
VBPR: Visual Bayesian Personalized Ranking from Implicit Feedback
Ruining He and Julian McAuley. 2015 · 2015
Earlier work this paper cites.
Image-Based Recommendations on Styles and Substitutes
Julian McAuley, Christopher Targett, Javen Qinfeng Shi, and Anton van den Hengel. 2015 · 2015
Earlier work this paper cites.
Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering
Ruining He and Julian McAuley. 2016 · 2016
Earlier work this paper cites.
Causal inference by using invariant prediction: identification and confidence intervals
Jonas Peters, Peter Bühlmann, and Nicolai Meinshausen. 2016 · 2016
Earlier work this paper cites.
Attentive Collaborative Filtering: Multimedia Recommendation with Item- and Component-Level Attention
Jingyuan Chen, Hanwang Zhang, Xiangnan He, Liqiang Nie, Wei Liu, and Tat-Seng Chua. 2017 · 2017
Earlier work this paper cites.
Visually-Aware Fashion Recommendation and Design with Generative Image Models
Wang-Cheng Kang, Chen Fang, Zhaowen Wang, and Julian McAuley. 2017 · 2017
Earlier work this paper cites.
DropoutNet: Addressing Cold Start in Recommender Systems
Maksims Volkovs, Guangwei Yu, and Tomi Poutanen. 2017 · 2017
Earlier work this paper cites.
xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems
Jianxun Lian, Xiaohuan Zhou, Fuzheng Zhang, Zhongxia Chen, Xing Xie, and Guang zhong Sun. 2018 · 2018
Earlier work this paper cites.
Manifold Mixup: Better Representations by Interpolating Hidden States
Vikas Verma, Alex Lamb, Christopher Beckham, Amir Najafi, Ioannis Mitliagkas, David Lopez-Paz, and Yoshua Bengio. 2018 · 2018
Earlier work this paper cites.
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang, Moustapha Cissé, Yann Dauphin, and David Lopez-Paz. 2018 · 2018
Earlier work this paper cites.
Invariant Risk Minimization
Martín Arjovsky, Léon Bottou, Ishaan Gulrajani, and David Lopez-Paz. 2019 · 2019
Cited alongside, same era.
MMGCN: Multi-modal Graph Convolution Network for Personalized Recommendation of Micro-video
Yin wei Wei, Xiang Wang, Liqiang Nie, Xiangnan He, Richang Hong, and Tat-Seng Chua. 2019 · 2019
Cited alongside, same era.
A first public dataset from Brazilian twitter and news on COVID-19 in Portuguese
Tiago de Melo and Carlos M.S. Figueiredo. 2020 · 2020
Cited alongside, same era.
How to Learn Item Representation for Cold-Start Multimedia Recommendation?
Xiaoyu Du, Xiang Wang, Xiangnan He, Zechao Li, Jinhui Tang, and Tat-Seng Chua. 2020 · 2020
Cited alongside, same era.
Out-of-Distribution Generalization via Risk Extrapolation (REx)
David Krueger, Ethan Caballero, Jörn-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Rémi Le Priol, and Aaron C. Courville. 2020 · 2020
Cited alongside, same era.
A Survey on Accuracy-Oriented Neural Recommendation: From Collaborative Filtering to Information-Rich Recommendation
Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, and Meng Wang. 2021b · 2021
Later among the works it cites.
Mining Latent Structures for Multimedia Recommendation
Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Shuhui Wang, and Liang Wang. 2021 · 2021
Later among the works it cites.
Generative Adversarial Framework for Cold-Start Item Recommendation
Hao Chen, Zefan Wang, Feiran Huang, Xiao Huang, Yue Xu, Yishi Lin, Peng He, and Zhoujun Li. 2022a · 2022
Later among the works it cites.
When Does Group Invariant Learning Survive Spurious Correlations?
Yimeng Chen, Ruibin Xiong, Zhi-Ming Ma, and Yanyan Lan. 2022b · 2022
Later among the works it cites.
Invariant Representation Learning for Multimedia Recommendation
Xiaoyu Du, Zike Wu, Fuli Feng, Xiangnan He, and Jinhui Tang. 2022 · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Xingchen Li, Xiang Wang, Xiangnan He, Long Chen, Jun Xiao, and Tat-Seng Chua. 2020 · 2020
Cited alongside, same era.
Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback
Yin wei Wei, Xiang Wang, Liqiang Nie, Xiangnan He, and Tat-Seng Chua. 2020 · 2020
Cited alongside, same era.
DiffNet++: A Neural Influence and Interest Diffusion Network for Social Recommendation
Le Wu, Junwei Li, Peijie Sun, Richang Hong, Yong Ge, and Meng Wang. 2020 · 2020
Cited alongside, same era.
Recommendation for New Users and New Items via Randomized Training and Mixture-of-Experts Transformation
Ziwei Zhu, Shahin Sefati, Parsa Saadatpanah, and James Caverlee. 2020 · 2020
Cited alongside, same era.
Environment inference for invariant learning
Elliot Creager, Jörn-Henrik Jacobsen, and Richard Zemel. 2021 · 2021
Cited alongside, same era.
Heterogeneous Risk Minimization
Jiashuo Liu, Zheyuan Hu, Peng Cui, B. Li, and Zheyan Shen. 2021 · 2021
Cited alongside, same era.
Unshuffling data for improved generalization in visual question answering
Damien Teney, Ehsan Abbasnejad, and Anton van den Hengel. 2021 · 2021
Cited alongside, same era.
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness
Francesco Pinto, Harry Yang, Ser Nam Lim, Philip H. S. Torr, and Puneet Kumar Dokania. 2022 · 2022
Later among the works it cites.
Invariant Preference Learning for General Debiasing in Recommendation
Zimu Wang, Yue He, Jiashuo Liu, Wenchao Zou, Philip S. Yu, and Peng Cui. 2022 · 2022
Later among the works it cites.
A Tale of Two Graphs: Freezing and Denoising Graph Structures for Multimodal Recommendation
Xin Zhou and Zhiqi Shen. 2022 · 2022
Later among the works it cites.
GoRec: A Generative Cold-Start Recommendation Framework
Haoyue Bai, Min Hou, Le Wu, Yonghui Yang, Richang Hong, and Meng Wang. 2023 · 2023
Later among the works it cites.
Multi-Modal Self-Supervised Learning for Recommendation
Wei Wei, Chao Huang, Lianghao Xia, and Chuxu Zhang. 2023 · 2023
Later among the works it cites.
Mining Stable Preferences: Adaptive Modality Decorrelation for Multimedia Recommendation
Jinghao Zhang, Qiang Liu, Shu Wu, and Liang Wang. 2023a · 2023
Later among the works it cites.
Latent Structure Mining With Contrastive Modality Fusion for Multimedia Recommendation
Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu, and Liang Wang. 2023b · 2023
Later among the works it cites.
Contrastive Collaborative Filtering for Cold-Start Item Recommendation
Zhihui Zhou, Lili Zhang, and Ning Yang. 2023 · 2023
Later among the works it cites.
Temporally and Distributionally Robust Optimization for Cold-start Recommendation
Xinyu Lin, Wenjie Wang, Jujia Zhao, Yongqi Li, Fuli Feng, and Tat-Seng Chua. 2024 · 2024
Closest in time.