Linglong Kong

9

Papers

3

Total Citations

Papers (9)

CBMA: Improving Conformal Prediction through Bayesian Model Averaging

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

Tuning-free Estimation and Inference of Cumulative Distribution Function under Local Differential Privacy

Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data

Gaussian Differential Privacy on Riemannian Manifolds

Distributional Reinforcement Learning for Efficient Exploration

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