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Generalization in the Face of Adaptivity: A Bayesian Perspective
However, differential privacy's worst-case nature entails scaling such noise to the range of the queries even for
Generalization in the Face of Adaptivity: A Bayesian Perspective
However, differential privacy's worst-case nature entails scaling such noise to the range of the queries even for
Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification
Uncertainty Quantification (UQ) is crucial for reliable image segmentation.
Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits
Contextual bandit is a widely used model for sequential decision making.
Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits
Contextual bandit is a widely used model for sequential decision making.
Robust Knowledge Transfer in Tiered RL
We identify a natural and necessary condition called the "Optimal
Adaptive Linear Estimating Equations
Sequential data collection has emerged as a widely adopted technique for enhancing the efficiency of data gathering processes. Despite its advantages, such data collection mechanism often introduces complexities to the statistical inference procedure.