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Selection bias

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Showing 301–350 of 365 papers

TitleStatusHype
Large-scale Causal Approaches to Debiasing Post-click Conversion Rate Estimation with Multi-task Learning—0
Entire Space Multi-Task Modeling via Post-Click Behavior Decomposition for Conversion Rate Prediction—0
More Powerful Selective Kernel Tests for Feature SelectionCode0
Co-Mining: Deep Face Recognition With Noisy Labels—0
Debiased Bayesian inference for average treatment effectsCode0
Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit FeedbackCode0
AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks—0
To Model or to Intervene: A Comparison of Counterfactual and Online Learning to Rank from User InteractionsCode0
Adjustment Criteria for Recovering Causal Effects from Missing Data—0
Statistical Learning from Biased Training Samples—0
A Debiased MDI Feature Importance Measure for Random ForestsCode0
Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm EvaluationCode0
Pre-training of Graph Augmented Transformers for Medication RecommendationCode0
Are sample means in multi-armed bandits positively or negatively biased?—0
Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching DatasetsCode0
Learning from Positive and Unlabeled Data with a Selection Bias—0
Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational DataCode0
State-Building through Public Land Disposal? An Application of Matrix Completion for Counterfactual PredictionCode0
Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-based Approach—0
On the bias, risk and consistency of sample means in multi-armed bandits—0
Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias—0
Selection and the Distribution of Female Hourly Wages in the U.S—0
Uniform Convergence Bounds for Codec Selection—0
Representation Learning for Treatment Effect Estimation from Observational DataCode0
A Simple Way to Deal with Cherry-picking—0
Beyond the Selected Completely At Random Assumption for Learning from Positive and Unlabeled DataCode0
Correcting the Triplet Selection Bias for Triplet LossCode0
Unknown Examples & Machine Learning Model Generalization—0
Learning under selective labels in the presence of expert consistency—0
Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm DesignCode0
Importance Weighted Generative Networks—0
Causal programming: inference with structural causal models as finding instances of a relation—0
Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion RateCode0
Effects of sampling skewness of the importance-weighted risk estimator on model selectionCode0
Inference on a Distribution from Noisy Draws—0
Learning Optimal Policies from Observational Data—0
Distinguishing Cause from Effect Using Quantiles: Bivariate Quantile Causal DiscoveryCode0
Bayesian Nonparametric Causal Inference: Information Rates and Learning Algorithms—0
Robust importance-weighted cross-validation under sample selection biasCode0
Causally Regularized Learning with Agnostic Data Selection Bias—0
Nonparametric Marginal Analysis of Recurrent Events Data under Competing Risks—0
Target contrastive pessimistic risk for robust domain adaptationCode0
A Comparison of Resampling and Recursive Partitioning Methods in Random Forest for Estimating the Asymptotic Variance Using the Infinitesimal Jackknife—0
Deep Counterfactual Networks with Propensity-DropoutCode0
Selective Inference for Change Point Detection in Multi-dimensional Sequences—0
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian ProcessesCode0
Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods—0
Unbiased split variable selection for random survival forests using maximally selected rank statistics—0
Reliable Baselines for Sentiment Analysis in Resource-Limited Languages: The Serbian Movie Review Dataset—0
Selective Inference Approach for Statistically Sound Predictive Pattern Mining—0
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