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Optimal design of experiments for Bayesian inverse problems has recently gained wide popularity and attracted much attention, especially in the computational science and Bayesian inversion communities. An optimal design maximizes a…

Optimization and Control · Mathematics 2023-05-09 Ahmed Attia , Sven Leyffer , Todd Munson

We characterize $D$-optimal designs in the two-dimensional Poisson regression model with synergetic interaction and provide an explicit proof. The proof is based on the idea of reparameterization of the design region in terms of contours of…

Statistics Theory · Mathematics 2021-06-17 Fritjof Freise , Ulrike Graßhoff , Frank Röttger , Rainer Schwabe

We extend the randomization-based causal inference framework in Dasgupta et al. (2015) for general 2^K factorial designs, and demonstrate the equivalence between regression-based and randomization-based inferences. Consequently, we justify…

Methodology · Statistics 2016-02-15 Jiannan Lu

Second-order optimality conditions of the bilevel programming problems are dependent on the second-order directional derivatives of the value functions or the solution mappings of the lower level problems under some regular conditions,…

Optimization and Control · Mathematics 2023-07-24 Xiang Liu , Mengwei Xu , Liwei Zhang

This paper considers the design of observational longitudinal studies with a continuous response and a binary time-invariant exposure, where, typically, the exposure is unbalanced, the mean response in the two groups differs at baseline and…

Methodology · Statistics 2022-09-27 Xavier Basagana , Donna Spiegelman

For paired comparison experiments involving competing options described by two-level attributes several different methods of constructing designs having block paired observations under the main effects model are presented. These designs are…

Methodology · Statistics 2019-10-16 Eric Nyarko

We consider a bilinear optimal control for an evolution equation involving the fractional Laplace operator of order $0<s<1$. We first give some existence and uniqueness results for the considered evolution equation. Next, we establish some…

Optimization and Control · Mathematics 2024-11-26 Gisèle Mophou , Cyrille Kenne , Mahamadi Warma

We present a unified deterministic approach for experimental design problems using the method of interlacing polynomials. Our framework recovers the best-known approximation guarantees for the well-studied D/A/E-design problems with simple…

Data Structures and Algorithms · Computer Science 2024-10-16 Lap Chi Lau , Robert Wang , Hong Zhou

Optimal experiment design for parameter estimation is a research topic that has been in the interest of various studies. A key problem in optimal input design is that the optimal input depends on some unknown system parameters that are to…

Systems and Control · Computer Science 2019-04-17 Lirong Huang , Håkan Hjalmarsson , László Gerencsér

Given n experiment subjects with potentially heterogeneous covariates and two possible treatments, namely active treatment and control, this paper addresses the fundamental question of determining the optimal accuracy in estimating the…

Machine Learning · Statistics 2024-11-13 Jiachun Li , David Simchi-Levi , Yunxiao Zhao

We investigate optimal discrimination between two projective quantum measurements on a single qubit. We consider scenario where the measurement that should be identified can be performed twice and we show that adaptive discrimination…

Quantum Physics · Physics 2015-05-14 Jaromir Fiurasek , Michal Micuda

Significant evidence has become available that emphasizes the importance of personalization in medicine. In fact, it has become a common belief that personalized medicine is the future of medicine. The core of personalized medicine is the…

Methodology · Statistics 2020-04-30 Qiong Zhang , Amin Khademi , Yongjia Song

The numerical performance of algorithms can be studied using test sets or procedures that generate such problems. This paper proposes various methods for generating linear, semidefinite, and second-order cone optimization problems.…

Optimization and Control · Mathematics 2023-02-03 Mohammadhossein Mohammadisiahroudi , Ramin Fakhimi , Brandon Augustino , Tamás Terlaky

For run sizes that are a multiple of four, the literature offers many two-level designs that are D- and A-optimal for the main-effects model and minimize the aliasing between main effects and interaction effects and among interaction…

Methodology · Statistics 2025-12-25 Mohammed Saif Ismail Hameed , Jose Núñez Ares , Eric D. Schoen , Peter Goos

Data collection costs can vary widely across variables in data science tasks. Two-phase designs can be employed to save data collection costs. This paper considers the two-phase studies where inexpensive variables are collected for all…

Methodology · Statistics 2025-12-04 Ruoyu Wang , Qihua Wang , Wang Miao

In small sample studies with binary outcome data, use of a normal approximation for hypothesis testing can lead to substantial inflation of the type-I error-rate. Consequently, exact statistical methods are necessitated, and accordingly,…

Methodology · Statistics 2017-11-29 Michael Grayling , Adrian Mander , James Wason

Primarily motivated by the drug development process, several publications have now presented methodology for the design of multi-arm multi-stage experiments with normally distributed outcome variables of known variance. Here, we extend…

Methodology · Statistics 2017-12-04 Michael Grayling , James Wason , Adrian Mander

We discuss the second-order differential uniformity of vectorial Boolean functions. The closely related notion of second-order zero differential uniformity has recently been studied in connection to resistance to the boomerang attack. We…

Information Theory · Computer Science 2024-10-02 Connor O'Reilly , Ana Sălăgean

This paper analytically investigates the optimal design of gamma degradation tests, including the number of test units, the number of inspections, and inspection times. We first derive optimal designs with periodic inspection times under…

Methodology · Statistics 2025-08-14 Hung-Ping Tung , Yu-Wen Chen

In recent years methods from optimal linear experimental design have been leveraged to obtain state of the art results for linear bandits. A design returned from an objective such as $G$-optimal design is actually a probability distribution…

Machine Learning · Computer Science 2021-05-13 Romain Camilleri , Julian Katz-Samuels , Kevin Jamieson
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