unbiased estimator

Experimentation on Endogenous Graphs AAAI 2026 Improving Value-based Process Verifier via Low-Cost Variance Reduction AAAI 2026 Statistical Learning from Attribution Sets COLT 2026 Confidence-based Estimators for Predictive Performance in Model Monitoring (Abstract Reprint) IJCAI 2025 Doubly Optimal Policy Evaluation for Reinforcement Learning ICLR 2025 How Much is Unseen Depends Chiefly on Information About the Seen ICLR 2025 Variational Combinatorial Sequential Monte Carlo for Bayesian Phylogenetics in Hyperbolic Space AISTATS 2025 An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations NeurIPS 2024 General Graph Random Features ICLR 2024 On Differentially Private U Statistics NeurIPS 2024 On Sampling Strategies for Spectral Model Sharding NeurIPS 2024 Unbiased Estimator for Distorted Conics in Camera Calibration CVPR 2024 End-to-end Training of Deep Boltzmann Machines by Unbiased Contrastive Divergence with Local Mode Initialization ICML 2023 Optimal randomized multilevel Monte Carlo for repeatedly nested expectations ICML 2023 Unbiased Multilevel Monte Carlo Methods for Intractable Distributions: MLMC Meets MCMC JMLR 2023 DALE: Differential Accumulated Local Effects for efficient and accurate global explanations ACML 2022 Multi-fidelity Monte Carlo: a pseudo-marginal approach NeurIPS 2022 The Poisson Binomial Mechanism for Unbiased Federated Learning with Secure Aggregation ICML 2022 Unbiased estimators for random design regression JMLR 2022 Efficient debiased evidence estimation by multilevel Monte Carlo sampling UAI 2021 Unbiased gradient estimation for variational auto-encoders using coupled Markov chains UAI 2021 Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies ICML 2021 Adaptive Shrinkage Estimation for Streaming Graphs NeurIPS 2020 Showing Your Work Doesn’t Always Work ACL 2020 Training Binary Neural Networks through Learning with Noisy Supervision ICML 2020