Modeling User Exposure in Recommendation

23 October 2015

Papers citing "Modeling User Exposure in Recommendation"

42 / 42 papers shown

Title
Exploiting Observation Bias to Improve Matrix Completion Yassir Jedra Sean Mann Charlotte Park Devavrat Shah 40 1 0 03 Jan 2025
Invariant debiasing learning for recommendation via biased imputation Ting Bai Weijie Chen Cheng Yang C. Shi 269 2 0 28 Dec 2024
A Thorough Performance Benchmarking on Lightweight Embedding-based Recommender Systems Hung Vinh Tran Tong Chen Quoc Viet Hung Nguyen Zi-Rui Huang Lizhen Cui Hongzhi Yin 50 1 0 25 Jun 2024
Impression-Aware Recommender Systems F. B. P. Maurera Maurizio Ferrari Dacrema P. Castells Paolo Cremonesi AI4TS 45 2 0 15 Aug 2023
Under-Counted Tensor Completion with Neural Incorporation of Attributes Shahana Ibrahim Xiao Fu R. Hutchinson Eugene Seo 41 1 0 05 Jun 2023
Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling Susobhan Ghosh Raphael Kim Prasidh Chhabria Raaz Dwivedi Predrag Klasjna Peng Liao Kelly Zhang Susan Murphy OffRL 32 8 0 11 Apr 2023
Pretrained Embeddings for E-commerce Machine Learning: When it Fails and Why? Da Xu Bo Yang 30 3 0 09 Apr 2023
Item Graph Convolution Collaborative Filtering for Inductive Recommendations Edoardo DÁmico Khalil Muhammad E. Tragos Barry Smyth N. Hurley A. Lawlor GNN 32 6 0 28 Mar 2023
Unbiased Learning to Rank with Biased Continuous Feedback Yi Ren Hongyan Tang Siwen Zhu CML 25 7 0 08 Mar 2023
Semi-decentralized Federated Ego Graph Learning for Recommendation Liang Qu Ningzhi Tang Ruiqi Zheng Quoc Viet Hung Nguyen Zi Huang Yuhui Shi Hongzhi Yin FedML 77 51 0 10 Feb 2023
Debiasing the Cloze Task in Sequential Recommendation with Bidirectional Transformers Khalil Damak Sami Khenissi O. Nasraoui BDL 37 7 0 22 Jan 2023
Biases in Scholarly Recommender Systems: Impact, Prevalence, and Mitigation Michael Färber Melissa Coutinho Shuzhou Yuan 34 7 0 18 Jan 2023
Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection Qiaoyu Tan Xin Zhang Ninghao Liu Daochen Zha Li Li Rui Chen Soo-Hyun Choi Xia Hu 48 41 0 23 Dec 2022
Interpretable Node Representation with Attribute Decoding Xiaohui Chen Xi Chen Liping Liu 37 4 0 03 Dec 2022
BeGin: Extensive Benchmark Scenarios and An Easy-to-use Framework for Graph Continual Learning Jihoon Ko Shinhwan Kang Taehyung Kwon Heechan Moon Kijung Shin CLL 46 7 0 26 Nov 2022
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders Xiaohan Li Zheng Liu Luyi Ma Kaushiki Nag Stephen D. Guo Philip Yu Kannan Achan CML 32 6 0 16 Nov 2022
TuneUp: A Simple Improved Training Strategy for Graph Neural Networks Weihua Hu Kaidi Cao Kexin Huang E-Wen Huang Karthik Subbian Kenji Kawaguchi J. Leskovec 41 0 0 26 Oct 2022
FedGRec: Federated Graph Recommender System with Lazy Update of Latent Embeddings Junyi Li Heng-Chiao Huang FedML 24 6 0 25 Oct 2022
KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems Chongming Gao Shijun Li Wenqiang Lei Jiawei Chen Biao Li Peng Jiang Xiangnan He Jiaxin Mao Tat-Seng Chua 37 131 0 22 Feb 2022
Supervised Contrastive Learning for Recommendation Chun Yang 19 37 0 10 Jan 2022
A Multi-Strategy based Pre-Training Method for Cold-Start Recommendation Bowen Hao Hongzhi Yin Jing Zhang Cuiping Li Hong Chen 37 22 0 04 Dec 2021
Learning Robust Recommender from Noisy Implicit Feedback Wenjie Wang Fuli Feng Xiangnan He Liqiang Nie Tat-Seng Chua NoLa 25 3 0 02 Dec 2021
Identifiable Generative Models for Missing Not at Random Data Imputation Chao Ma Cheng Zhang 36 34 0 27 Oct 2021
Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives Zida Cheng Chuanwei Ruan Siheng Chen Sushant Kumar Ya Zhang 27 16 0 23 Oct 2021
Recommender systems based on graph embedding techniques: A comprehensive review Yue Deng 49 22 0 20 Sep 2021
Debiased Explainable Pairwise Ranking from Implicit Feedback Khalil Damak Sami Khenissi O. Nasraoui 29 16 0 30 Jul 2021
Correcting Exposure Bias for Link Recommendation Shantanu Gupta Hao Wang Zachary Chase Lipton Bernie Wang CML 39 34 0 13 Jun 2021
Scalable Personalised Item Ranking through Parametric Density Estimation Riku Togashi Masahiro Kato Mayu Otani T. Sakai Shiníchi Satoh 40 0 0 11 May 2021
AutoDebias: Learning to Debias for Recommendation Jiawei Chen Hande Dong Yang Qiu Xiangnan He Xin Xin Liang Chen Guli Lin Keping Yang CML 34 200 0 10 May 2021
Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering Jingtao Ding Yuhan Quan Quanming Yao Yong Li Depeng Jin 19 97 0 07 Sep 2020
Counterfactual Evaluation of Slate Recommendations with Sequential Reward Interactions James McInerney B. Brost Praveen Chandar Rishabh Mehrotra Ben Carterette BDL CML OffRL 121 55 0 25 Jul 2020
Fast Adaptively Weighted Matrix Factorization for Recommendation with Implicit Feedback Jiawei Chen Can Wang Sheng Zhou Qihao Shi Jingbang Chen Yan Feng Chun-Yen Chen OffRL 51 56 0 04 Mar 2020
Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach Lei Chen Le Wu Richang Hong Kun Zhang Meng Wang GNN 36 493 0 28 Jan 2020
Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption Wei-Ying Ma George H. Chen 23 49 0 28 Oct 2019
Large-scale Causal Approaches to Debiasing Post-click Conversion Rate Estimation with Multi-task Learning Wenhao Zhang Wentian Bao Xiao-Yang Liu Keping Yang Quan Lin Hong Wen Ramin Ramezani CML 29 104 0 16 Oct 2019
Relaxed Softmax for learning from Positive and Unlabeled data Ugo Tanielian Flavian Vasile 18 9 0 17 Sep 2019
Adversarial Personalized Ranking for Recommendation Xiangnan He Zhankui He Xiaoyu Du Tat-Seng Chua 32 395 0 12 Aug 2018
How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility A. Chaney Brandon M Stewart Barbara E. Engelhardt CML 169 314 0 30 Oct 2017
Dynamic Bernoulli Embeddings for Language Evolution Maja R. Rudolph David M. Blei BDL 24 34 0 23 Mar 2017
Recurrent Poisson Factorization for Temporal Recommendation Seyed Abbas Hosseini Keivan Alizadeh-Vahid Ali Khodadadi A. Arabzadeh Mehrdad Farajtabar H. Zha Hamid R. Rabiee 22 56 0 04 Mar 2017
Exponential Family Embeddings Maja R. Rudolph Francisco J. R. Ruiz Stephan Mandt David M. Blei 30 107 0 02 Aug 2016
Recommendations as Treatments: Debiasing Learning and Evaluation Tobias Schnabel Adith Swaminathan Ashudeep Singh Navin Chandak Thorsten Joachims CML 6 675 0 17 Feb 2016