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stat.ML2024★ 1 cited
Bayesian Bandit Algorithms with Approximate Inference in Stochastic Linear Bandits
Ziyi Huang, Henry Lam, Haofeng Zhang
Bayesian bandit algorithms with approximate Bayesian inference have been widely used in real-world applications. Despite the superior practical performance, their theoretical justi…
stat.ML2023★ 2 cited
Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks
Ziyi Huang, Henry Lam, Haofeng Zhang
Uncertainty quantification (UQ) is important for reliability assessment and enhancement of machine learning models. In deep learning, uncertainties arise not only from data, but al…
stat.ML2021★ 8 cited
Learning Prediction Intervals for Regression: Generalization and Calibration
Haoxian Chen, Ziyi Huang, Henry Lam +2
We study the generation of prediction intervals in regression for uncertainty quantification. This task can be formalized as an empirical constrained optimization problem that mini…