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Assessing Replicability Via Multi-lab Collaborations 07-Mar-2022 09:00 AM PST - 07-Mar-2022 09:25 AM PST
Showing 1 - 18 of 18 matches
Datamodels: Predicting Predictions with Training Data
Date: March 07, 2022
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Domain Adaptation Under Structural Causal Models
Date: March 07, 2022
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Evaluating Replicability: Considerations for Analyses and Implications for Design
Date: March 07, 2022
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Evaluating Replicability: Considerations for Analyses and Implications for Design
Date: March 07, 2022
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Disentangling Confounding and Nonsense Associations Due to Dependence
Date: March 08, 2022
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Prospects and Perils of Interpolating Models
Date: March 09, 2022
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Distributionally Robust Bayesian Nonparametric Regression
Date: March 09, 2022
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Calibrated Inference: Statistical Inference that Accounts for Both Sampling Uncertainty and Distributional Uncertainty
Date: March 09, 2022
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Calibrated Inference: Statistical Inference that Accounts for Both Sampling Uncertainty and Distributional Uncertainty
Date: March 09, 2022
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Assessing External Validity Over Worst-Case Subpopulations
Date: March 09, 2022
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Veridical Network Embedding
Date: March 10, 2022
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Sim2Real Transfer in Robotics: Thoughts on Model Pruning and Robust Visual Transfer
Date: March 10, 2022
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Predicting Out-of-Distribution Error with the Projection Norm
Date: March 10, 2022
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Structured Adaptation & Deep Learning: When Prediction Yields Adaptation
Date: March 10, 2022
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Near-Optimal Compression in Near-Linear Time
Date: March 08, 2022
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A Precise High-Dimensional Asymptotic Theory for AdaBoost
Date: March 09, 2022
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Bayesian Nonparametric Models for Treatment Effect Heterogeneity: Model Parameterization, Prior Choice, and Posterior Summarization
Date: March 10, 2022
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Distribution Generalization in Underidentified Causal Models
Date: March 08, 2022
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