Doubly robust estimation in missing data and causal inference models
PulseAugur coverage of Doubly robust estimation in missing data and causal inference models — every cluster mentioning Doubly robust estimation in missing data and causal inference models across labs, papers, and developer communities, ranked by signal.
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New model optimizes cross-border fulfillment center selection
Researchers have developed a new optimization framework called the Cross-Border Fulfillment Center Selection Model. This model integrates forecasting, doubly robust estimation, and linear programming to identify the mos…
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New VOCEM estimator improves off-policy evaluation for contextual bandits
Researchers have introduced a new method for off-policy evaluation (OPE) in contextual bandit policies called Variance Optimal-CEM (VOCEM). This approach aims to reduce the high variance associated with action-level imp…
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New methods proposed for counterfactual evaluation of ad ranking models
This paper introduces new methods for evaluating ad ranking models, focusing on counterfactual evaluation. It proposes using Inverse Propensity Scoring (IPS) and Doubly Robust (DR) estimators to assess model performance…
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New research advances off-policy evaluation techniques for ML
Two new research papers explore advanced techniques for off-policy evaluation (OPE) in machine learning, a critical process for assessing the performance of new policies using existing data. The first paper introduces "…