Proportional Volume Sampling and Approximation Algorithms for A-Optimal Design

DOI10.1287/moor.2021.1129zbMath1489.68402OpenAlexW2788976390MaRDI QIDQ5085119

Uthaipon Tantipongpipat, Mohit Singh, Aleksandar Nikolov

Publication date: 27 June 2022

Published in: Mathematics of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1287/moor.2021.1129

zbMATH Keywords

design of experimentslinear regressionoptimal designapproximation algorithmsNP-hardness\(D\)-optimal design\(A\)-optimal designvolume samplinggeneralized ratio objectiveproportional volume sampling

Mathematics Subject Classification ID

Optimal statistical designs (62K05) Combinatorial optimization (90C27) Approximation algorithms (68W25)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A note on subset selection for matrices
• All convex invariant functions of hermitian matrices
• Subset selection for matrices
• On selecting a maximum volume sub-matrix of a matrix and related problems
• Invertibility of ``large submatrices with applications to the geometry of Banach spaces and harmonic analysis
• Eigenvalues and expanders
• Asymptotics of the chromatic index for multigraphs
• On the second eigenvalue of a graph
• The hardness of approximation: Gap location
• Simple multivariate polynomial multiplication
• An elementary proof of the restricted invertibility theorem
• The Geometry of Differential Privacy: The Small Database and Approximate Cases
• Determinantal Point Processes for Machine Learning
• Randomized Rounding for the Largest Simplex Problem
• RESTRICTED INVERTIBILITY AND THE BANACH–MAZUR DISTANCE TO THE CUBE
• Inequalities for Symmetric Functions and Hermitian Matrices
• Symmetric Means and Matrix Inequalities
• Matrix approximation and projective clustering via volume sampling
• Adaptive Sampling and Fast Low-Rank Matrix Approximation
• On some inequalities for elementary symmetric functions
• Sensor Selection via Convex Optimization
• An Alon-Boppana Type Bound for Weighted Graphs and Lowerbounds for Spectral Sparsification
• Twice-Ramanujan Sparsifiers
• Real stable polynomials and matroids: optimization and counting
• A generalization of permanent inequalities and applications in counting and optimization
• Optimal Design of Experiments
• Deterministic Feature Selection for K-Means Clustering
• Maximizing determinants under partition constraints
• On largest volume simplices and sub-determinants
• Approximating Hereditary Discrepancy via Small Width Ellipsoids
• Faster Subset Selection for Matrices and Applications
• A Randomized Rounding Approach to the Traveling Salesman Problem
• Optimal Column-Based Low-Rank Matrix Reconstruction
• A Measure of Asymptotic Efficiency for Tests of a Hypothesis Based on the sum of Observations
• John's decompositions: Selecting a large part
• Graph Sparsification by Effective Resistances

This page was built for publication: Proportional Volume Sampling and Approximation Algorithms for A-Optimal Design