Cover Image

Statistically Efficient Bayesian Sequential Experiment Design via Reinforcement Learning with Cross-Entropy Estimators

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Blau, Tom, Chades, Iadine, Dezfouli, Amir, Steinberg, Daniel, Bonilla, Edwin V.
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Approximate Nearest Neighbour Search on Dynamic Datasets: An Investigation
by: Harwood, Ben, et al.
Published: (2024)

Efficient Statistical Estimation for Sequential Adaptive Experiments with Implications for Adaptive Designs
by: Zhang, Wenxin, et al.
Published: (2025)

The Contextual Lasso: Sparse Linear Models via Deep Neural Networks
by: Thompson, Ryan, et al.
Published: (2023)

Optimal Stopping for Sequential Bayesian Experimental Design
by: Cheng, Chen, et al.
Published: (2025)

Causal Preference Elicitation
by: Bonilla, Edwin V., et al.
Published: (2026)

Beyond expected values: Making environmental decisions using value of information analysis when measurement outcome matters
by: Akinlotan, Morenikeji D., et al.
Published: (2023)

Goal-Oriented Sequential Bayesian Experimental Design for Causal Learning
by: Zhang, Zheyu, et al.
Published: (2025)

Sequential Design with Derived Win Statistics
by: Zhang, Baoshan, et al.
Published: (2024)

Constructing Bayesian Optimal Designs for Discrete Choice Experiments by Simulated Annealing
by: Mao, Yicheng, et al.
Published: (2024)

Bayesian Quantile Estimation and Regression with Martingale Posteriors
by: Fong, Edwin, et al.
Published: (2024)

Targeted Sequential Indirect Experiment Design
by: Ailer, Elisabeth, et al.
Published: (2024)

Recursive Nested Filtering for Efficient Amortized Bayesian Experimental Design
by: Iqbal, Sahel, et al.
Published: (2024)

Batch Sequential Experimental Design for Calibration of Stochastic Simulation Models
by: Sürer, Özge
Published: (2025)

bayesics: Core Statistical Methods via Bayesian Inference in R
by: Sewell, Daniel K., et al.
Published: (2026)

Sequential Experimental Designs for Kriging Model
by: Zheng, Ruonan, et al.
Published: (2026)

Bayesian Design of Experiments in the Presence of Nuisance Parameters
by: Golchi, Shirin, et al.
Published: (2025)

Gradient-Based Approximate Bayesian Inference with Entropy-Optimized Summary Statistics for Compartmental Models
by: Li, Xiahui, et al.
Published: (2024)

Efficient Active Learning Strategies for Computer Experiments
by: Song, Difan, et al.
Published: (2025)

Fully Bayesian Sequential Design for Mean Response Surface Prediction of Heteroscedastic Stochastic Simulations
by: Huang, Yuying, et al.
Published: (2025)

Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning
by: Shen, Wanggang, et al.
Published: (2021)

Sequentially-Rerandomized Switchback Experiments
by: Zeng, Zhenghao, et al.
Published: (2026)

Simulation Experiment Design for Calibration via Active Learning
by: Sürer, Özge
Published: (2024)

Pigeonhole Design: Balancing Sequential Experiments from an Online Matching Perspective
by: Zhao, Jinglong, et al.
Published: (2022)

Sequential Bayesian Registration for Functional Data
by: Kim, Yoonji, et al.
Published: (2022)

Topics in Nonparametric Bayesian Statistics
by: Hjort, Nils Lid
Published: (2026)

Bayesian Inference and the Principle of Maximum Entropy
by: Foley, Duncan K., et al.
Published: (2024)

AgroDesign: A Design-Aware Statistical Inference Framework for Agricultural Experiments in Python
by: Gul, Aqib
Published: (2026)

Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing
by: Wang, Jitao, et al.
Published: (2025)

Hedging in Sequential Experiments
by: Cook, Thomas, et al.
Published: (2024)

fdesigns: Bayesian Optimal Designs of Experiments for Functional Models in R
by: Michaelides, Damianos, et al.
Published: (2024)

Efficient Bayesian Estimation of Dynamic Structural Equation Models via State Space Marginalization
by: Sørensen, Øystein
Published: (2026)

The Bayesian Way: Uncertainty, Learning, and Statistical Reasoning
by: Sosa, Juan, et al.
Published: (2025)

Bayesian Transfer Learning for Enhanced Estimation and Inference
by: Lai, Daoyuan, et al.
Published: (2024)

Sequential design for surrogate modeling in Bayesian inverse problems
by: Lartaud, Paul, et al.
Published: (2024)

Estimating Treatment and Spillover Effects with the Ego-Cluster Experimental Design
by: Liu, Xiao, et al.
Published: (2026)

Globally-Optimal Greedy Experiment Selection for Active Sequential Estimation
by: Li, Xiaoou, et al.
Published: (2024)

A Scale-Invariant Entropy Statistic for Distance Distributions
by: Gewily, Mohamed
Published: (2026)

Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning
by: Wu, Xiangkun, et al.
Published: (2026)

Efficient Nested Simulation Experiment Design via the Likelihood Ratio Method
by: Feng, Mingbin Ben, et al.
Published: (2020)

Modern Statistical Models and Methods for Estimating Fatigue-Life and Fatigue-Strength Distributions from Experimental Data
by: Meeker, William Q., et al.
Published: (2022)