v1v2 (latest)

Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption

28 October 2019

Papers citing "Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption"

32 / 32 papers shown

Title
Optimal Transfer Learning for Missing Not-at-Random Matrix Completion Akhil Jalan Yassir Jedra Arya Mazumdar Soumendu Sundar Mukherjee Purnamrita Sarkar 505 0 0 28 Feb 2025
Collaborative Imputation of Urban Time Series through Cross-city Meta-learning Tong Nie Wei Ma Jian Sun Yu Yang Jiannong Cao AI4TS AI4CE 87 0 0 20 Jan 2025
Exploiting Observation Bias to Improve Matrix Completion Yassir Jedra Sean Mann Charlotte Park Devavrat Shah 458 1 0 03 Jan 2025
Learning Counterfactual Distributions via Kernel Nearest Neighbors Kyuseong Choi Jacob Feitelberg Anish Agarwal Raaz Dwivedi OOD OffRL 441 1 0 17 Oct 2024
Symmetric Matrix Completion with ReLU Sampling Huikang Liu Peng Wang Longxiu Huang Qing Qu Laura Balzano 81 3 0 09 Jun 2024
Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random Mingming Ha Xuewen Tao Wenfang Lin Qionxu Ma Wujiang Xu Lin Chen 84 2 0 24 May 2024
Doubly Robust Inference in Causal Latent Factor Models Alberto Abadie Anish Agarwal Raaz Dwivedi Abhin Shah CML OOD 92 3 0 18 Feb 2024
ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation Tong Nie Guoyang Qin Wei Ma Yuewen Mei Jiangming Sun AI4TS AI4CE 115 36 0 04 Dec 2023
Deep Generative Imputation Model for Missing Not At Random Data Jia-Lve Chen Yuanbo Xu Pengyang Wang Yongjian Yang SyDa 51 9 0 16 Aug 2023
Regression with Sensor Data Containing Incomplete Observations Takayuki Katsuki Takayuki Osogami 123 1 0 26 Apr 2023
Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions Abhineet Agarwal Anish Agarwal Suhas Vijaykumar CML 72 9 0 24 Mar 2023
Bilateral Self-unbiased Learning from Biased Implicit Feedback Jae-woong Lee Seongmin Park Joonseok Lee Jongwuk Lee CML 76 12 0 26 Jul 2022
Sequential Nature of Recommender Systems Disrupts the Evaluation Process Ali Shirali 52 4 0 26 May 2022
FragmGAN: Generative Adversarial Nets for Fragmentary Data Imputation and Prediction Fang Fang Shenliao Bao AI4CE GAN 57 7 0 09 Mar 2022
Identifiable Generative Models for Missing Not at Random Data Imputation Chao Ma Cheng Zhang 72 36 0 27 Oct 2021
Learning to Recommend Using Non-Uniform Data W. Chen Mohsen Bayati CML 68 1 0 21 Oct 2021
Causal Matrix Completion Anish Agarwal M. Dahleh Devavrat Shah Dennis Shen CML 461 54 0 30 Sep 2021
Matrix Completion of World Trade G. Gnecco Federico Nutarelli M. Riccaboni 17 0 0 08 Sep 2021
How Low Can We Go: Trading Memory for Error in Low-Precision Training Chengrun Yang Ziyang Wu Jerry Chee Christopher De Sa Madeleine Udell 60 2 0 17 Jun 2021
Correcting Exposure Bias for Link Recommendation Shantanu Gupta Hao Wang Zachary Chase Lipton Bernie Wang CML 80 35 0 13 Jun 2021
Matrix completion with data-dependent missingness probabilities Sohom Bhattacharya S. Chatterjee 127 20 0 04 Jun 2021
Enhanced Doubly Robust Learning for Debiasing Post-click Conversion Rate Estimation Siyuan Guo Lixin Zou Yiding Liu Wenwen Ye Suqi Cheng Shuaiqiang Wang Hechang Chen Dawei Yin Yi-Ju Chang 70 93 0 28 May 2021
Prediction in the presence of response-dependent missing labels Hyebin Song Garvesh Raskutti Rebecca Willett 18 0 0 25 Mar 2021
TenIPS: Inverse Propensity Sampling for Tensor Completion Chengrun Yang Lijun Ding Ziyang Wu Madeleine Udell 143 8 0 01 Jan 2021
On Model Identification and Out-of-Sample Prediction of Principal Component Regression: Applications to Synthetic Controls Anish Agarwal Devavrat Shah Dennis Shen 78 2 0 27 Oct 2020
Chemical Property Prediction Under Experimental Biases Yang Liu H. Kashima AI4CE 48 1 0 18 Sep 2020
Theoretical Modeling of the Iterative Properties of User Discovery in a Collaborative Filtering Recommender System Sami Khenissi M. Boujelbene O. Nasraoui 49 23 0 21 Aug 2020
NeuMiss networks: differentiable programming for supervised learning with missing values Marine Le Morvan Julie Josse Thomas Moreau Erwan Scornet Gaël Varoquaux 86 8 0 03 Jul 2020
not-MIWAE: Deep Generative Modelling with Missing not at Random Data Niels Bruun Ipsen Pierre-Alexandre Mattei J. Frellsen DRL 70 57 0 23 Jun 2020
On the Fairness of Randomized Trials for Recommendation with Heterogeneous Demographics and Beyond Zifeng Wang Xi Chen Rui Wen Shao-Lun Huang 130 1 0 25 Jan 2020
Towards Resolving Propensity Contradiction in Offline Recommender Learning Yuta Saito Masahiro Nomura OffRL 96 13 0 16 Oct 2019
Estimation and imputation in Probabilistic Principal Component Analysis with Missing Not At Random data Aude Sportisse Claire Boyer Julie Josse 112 29 0 06 Jun 2019