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Selection bias

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Showing 301–325 of 365 papers

TitleStatusHype
Learning to Bound Counterfactual Inference from Observational, Biased and Randomised DataCode0
Deep Counterfactual Networks with Propensity-DropoutCode0
The Structurally Complex with Additive Parent Causality (SCARY) DatasetCode0
A Double Machine Learning Approach for the Evaluation of COVID-19 Vaccine Effectiveness under the Test-Negative Design: Analysis of Québec Administrative DataCode0
Demographics Should Not Be the Reason of Toxicity: Mitigating Discrimination in Text Classifications with Instance WeightingCode0
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection BiasCode0
Automated Dependence PlotsCode0
Bounding Counterfactuals under Selection BiasCode0
Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect EstimationCode0
BOBA: Byzantine-Robust Federated Learning with Label SkewnessCode0
DIRAS: Efficient LLM Annotation of Document Relevance in Retrieval Augmented GenerationCode0
Bias Reduction via Cooperative Bargaining in Synthetic Graph Dataset GenerationCode0
Leveraging CORAL-Correlation Consistency Network for Semi-Supervised Left Atrium MRI SegmentationCode0
Batch-Mix Negative Sampling for Learning Recommendation RetrieversCode0
Does Interference Exist When Training a Once-For-All Network?Code0
Double Robust Semi-Supervised Inference for the Mean: Selection Bias under MAR Labeling with Decaying OverlapCode0
Doubly Calibrated Estimator for Recommendation on Data Missing Not At RandomCode0
Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm DesignCode0
LLM-Generated Feedback Supports Learning If Learners Choose to Use ItCode0
Effects of sampling skewness of the importance-weighted risk estimator on model selectionCode0
EGEAN: An Exposure-Guided Embedding Alignment Network for Post-Click Conversion EstimationCode0
Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit FeedbackCode0
Beyond the Selected Completely At Random Assumption for Learning from Positive and Unlabeled DataCode0
Local Constraint-Based Causal Discovery under Selection BiasCode0
Rethinking recidivism through a causal lensCode0
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