Bei Jiang

7

Papers

3

Total Citations

Papers (7)

CBMA: Improving Conformal Prediction through Bayesian Model Averaging

Intrinsic Benefits of Categorical Distributional Loss: Uncertainty-aware Regularized Exploration in Reinforcement Learning

Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data

Gaussian Differential Privacy on Riemannian Manifolds

Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization

Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy

Conformalized Fairness via Quantile Regression