| Learning From Missing Data Using Selection Bias in Movie Recommendation | Sep 30, 2015 | Collaborative FilteringMovie Recommendation | —Unverified | 0 | 0 |
| Learning from Positive and Unlabeled Data with a Selection Bias | May 1, 2019 | Selection bias | —Unverified | 0 | 0 |
| Learning Infomax and Domain-Independent Representations for Causal Effect Inference with Real-World Data | Feb 22, 2022 | Causal InferenceRepresentation Learning | —Unverified | 0 | 0 |
| Learning Optimal Policies from Observational Data | Feb 23, 2018 | Domain AdaptationSelection bias | —Unverified | 0 | 0 |
| Learning Overlapping Representations for the Estimation of Individualized Treatment Effects | Jan 14, 2020 | Generalization Boundsregression | —Unverified | 0 | 0 |
| Learning Sparse Causal Models is not NP-hard | Sep 26, 2013 | Causal DiscoveryModel Discovery | —Unverified | 0 | 0 |
| Learning under selective labels in the presence of expert consistency | Jul 2, 2018 | Data AugmentationDecision Making | —Unverified | 0 | 0 |
| Learning under Selective Labels with Data from Heterogeneous Decision-makers: An Instrumental Variable Approach | Jun 13, 2023 | Decision MakingSelection bias | —Unverified | 0 | 0 |
| Lee Bounds with a Continuous Treatment in Sample Selection | Nov 6, 2024 | Causal InferenceSelection bias | —Unverified | 0 | 0 |
| Low-Complexity Methods for Estimation After Parameter Selection | Jan 28, 2020 | Selection bias | —Unverified | 0 | 0 |
