HASOD: A Hybrid Adaptive Screening-Optimization Design for High-Dimensional Industrial Experiments
Fuente:
arXiv
Saved in:
| Main Author: | Pathak, Kumarjit |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adaptive Experimental Design Using Shrinkage Estimators
by: Rosenman, Evan T. R., et al.
Published: (2026)
by: Rosenman, Evan T. R., et al.
Published: (2026)
Cost-Aware Optimized Front-Door Experimental Design
by: Mareis, Leopold, et al.
Published: (2026)
by: Mareis, Leopold, et al.
Published: (2026)
Adaptive Long-Run Variance Thresholding for Sparse Covariance Estimation in High-Dimensional Time Series
by: Zhang, Wenhao, et al.
Published: (2026)
by: Zhang, Wenhao, et al.
Published: (2026)
Optimizing High-Dimensional Oblique Splits
by: Chi, Chien-Ming
Published: (2025)
by: Chi, Chien-Ming
Published: (2025)
Stronger Neyman Regret Guarantees for Adaptive Experimental Design
by: Noarov, Georgy, et al.
Published: (2025)
by: Noarov, Georgy, et al.
Published: (2025)
Adaptive and Stratified Subsampling for High-Dimensional Robust Estimation
by: Mittal, Prateek, et al.
Published: (2024)
by: Mittal, Prateek, et al.
Published: (2024)
Causal Inference with High-Dimensional Treatments
by: Kramer, Patrick, et al.
Published: (2026)
by: Kramer, Patrick, et al.
Published: (2026)
Covariance Regression with High-Dimensional Predictors
by: He, Yuheng, et al.
Published: (2024)
by: He, Yuheng, et al.
Published: (2024)
Design Stability in Adaptive Experiments: Implications for Treatment Effect Estimation
by: Sengupta, Saikat, et al.
Published: (2025)
by: Sengupta, Saikat, et al.
Published: (2025)
Efficient High-Dimensional Conditional Independence Testing
by: Banerjee, Bilol
Published: (2025)
by: Banerjee, Bilol
Published: (2025)
Robust Max Statistics for High-Dimensional Inference
by: Liu, Mingshuo, et al.
Published: (2024)
by: Liu, Mingshuo, et al.
Published: (2024)
Testing Separability of High-Dimensional Covariance Matrices
by: Sung, Bongjung, et al.
Published: (2025)
by: Sung, Bongjung, et al.
Published: (2025)
Sequential Correct Screening and Post-Screening Inference
by: Toyoda, Masaki, et al.
Published: (2025)
by: Toyoda, Masaki, et al.
Published: (2025)
Characterizing Finite-Dimensional Posterior Marginals in High-Dimensional GLMs via Leave-One-Out
by: Sáenz, Manuel, et al.
Published: (2025)
by: Sáenz, Manuel, et al.
Published: (2025)
Profiled Transfer Learning for High Dimensional Linear Model
by: Lin, Ziqian, et al.
Published: (2024)
by: Lin, Ziqian, et al.
Published: (2024)
Application of Random Matrix Theory in High-Dimensional Statistics
by: Bhattacharyya, Swapnaneel, et al.
Published: (2024)
by: Bhattacharyya, Swapnaneel, et al.
Published: (2024)
High Dimensional Logistic Regression Under Network Dependence
by: Mukherjee, Somabha, et al.
Published: (2021)
by: Mukherjee, Somabha, et al.
Published: (2021)
Expected Weighted D-optimal Designs for Experiments with Mixed Factors
by: Lin, Siting, et al.
Published: (2025)
by: Lin, Siting, et al.
Published: (2025)
Statistical Inference on High Dimensional Gaussian Graphical Regression Models
by: Meng, Xuran, et al.
Published: (2024)
by: Meng, Xuran, et al.
Published: (2024)
Frequency Domain Statistical Inference for High-Dimensional Time Series
by: Krampe, Jonas, et al.
Published: (2022)
by: Krampe, Jonas, et al.
Published: (2022)
High Dimensional Bootstrap and Asymptotic Expansion for the $k$-th Largest Coordinate
by: Feng, Long
Published: (2026)
by: Feng, Long
Published: (2026)
Sparse Data-Driven Random Projection in Regression for High-Dimensional Data
by: Parzer, Roman, et al.
Published: (2023)
by: Parzer, Roman, et al.
Published: (2023)
High-Dimensional Single-Index Models: Link Estimation and Marginal Inference
by: Sawaya, Kazuma, et al.
Published: (2024)
by: Sawaya, Kazuma, et al.
Published: (2024)
Testing High-Dimensional Mediation Effect with Arbitrary Exposure-Mediator Coefficients
by: Lin, Yinan, et al.
Published: (2023)
by: Lin, Yinan, et al.
Published: (2023)
A Debiased Estimator for the Mediation Functional in Ultra-High-Dimensional Setting in the Presence of Interaction Effects
by: Bo, Shi, et al.
Published: (2024)
by: Bo, Shi, et al.
Published: (2024)
Minimax and Bayes Optimal Adaptive Experimental Design for Treatment Choice
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
Adaptive Weight Learning for Multiple Outcome Optimization With Continuous Treatment
by: Wang, Chang, et al.
Published: (2024)
by: Wang, Chang, et al.
Published: (2024)
The Optimality of Blocking Designs in Equally and Unequally Allocated Randomized Experiments with General Response
by: Azriel, David, et al.
Published: (2022)
by: Azriel, David, et al.
Published: (2022)
High-Dimensional Block Diagonal Covariance Structure Detection Using Singular Vectors
by: Bauer, Jan O.
Published: (2022)
by: Bauer, Jan O.
Published: (2022)
High-Dimensional Covariate-Dependent Discrete Graphical Models and Dynamic Ising Models
by: Roach, Lyndsay, et al.
Published: (2025)
by: Roach, Lyndsay, et al.
Published: (2025)
Simultaneous Inference in Multiple Matrix-Variate Graphs for High-Dimensional Neural Recordings
by: Liu, Zongge, et al.
Published: (2024)
by: Liu, Zongge, et al.
Published: (2024)
Debiased Inference for High-Dimensional Regression Models Based on Profile M-Estimation
by: Wang, Yi, et al.
Published: (2025)
by: Wang, Yi, et al.
Published: (2025)
A Two-Step Projection-Based Goodness-of-Fit Test for Ultra-High Dimensional Sparse Regressions
by: Tan, Falong, et al.
Published: (2024)
by: Tan, Falong, et al.
Published: (2024)
To Study Properties of a Known Procedure in Adaptive Sequential Sampling Design
by: Kundu, Sampurna, et al.
Published: (2024)
by: Kundu, Sampurna, et al.
Published: (2024)
Sigmoid-FTRL: Design-Based Adaptive Neyman Allocation for AIPW Estimators
by: Chen, Fangyi, et al.
Published: (2025)
by: Chen, Fangyi, et al.
Published: (2025)
Learning What to Learn: Experimental Design when Combining Experimental with Observational Evidence
by: Epanomeritakis, Aristotelis, et al.
Published: (2025)
by: Epanomeritakis, Aristotelis, et al.
Published: (2025)
On the Efficiency of Highly Stratified Experiments
by: Bai, Yuehao, et al.
Published: (2023)
by: Bai, Yuehao, et al.
Published: (2023)
A General Design-Based Framework and Estimator for Randomized Experiments
by: Harshaw, Christopher, et al.
Published: (2022)
by: Harshaw, Christopher, et al.
Published: (2022)
Strong Oracle Guarantees for Partial Penalized Tests of High Dimensional Generalized Linear Models
by: Jacobson, Tate
Published: (2024)
by: Jacobson, Tate
Published: (2024)
A Shrinkage Likelihood Ratio Test for High-Dimensional Subgroup Analysis with a Logistic-Normal Mixture Model
by: Takeishi, Shota
Published: (2023)
by: Takeishi, Shota
Published: (2023)
Similar Items
-
Adaptive Experimental Design Using Shrinkage Estimators
by: Rosenman, Evan T. R., et al.
Published: (2026) -
Cost-Aware Optimized Front-Door Experimental Design
by: Mareis, Leopold, et al.
Published: (2026) -
Adaptive Long-Run Variance Thresholding for Sparse Covariance Estimation in High-Dimensional Time Series
by: Zhang, Wenhao, et al.
Published: (2026) -
Optimizing High-Dimensional Oblique Splits
by: Chi, Chien-Ming
Published: (2025) -
Stronger Neyman Regret Guarantees for Adaptive Experimental Design
by: Noarov, Georgy, et al.
Published: (2025)