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Optimal Deterministic Group Testing Algorithms to Estimate the Number of Defectives
[article]
2020
arXiv
pre-print
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We study the problem of estimating the number of defective items d within a pile of n elements up to a multiplicative factor of Δ>1, using deterministic group testing algorithms. ...
For the adaptive deterministic settings, our results show that, any algorithm for estimating the defectives number up to a multiplicative factor of Δ must make at least Ω((D/Δ^2)log (n/D) ) tests. ...
For the adaptive deterministic settings, our results show that, any algorithm for estimating the defectives number up to a multiplicative factor of ∆ must make at least Ω (D/∆ 2 ) log(n/D) tests. ...
arXiv:2009.02520v1
fatcat:qxuypzqru5e5vbburh5ayhr34m
Optimal Randomized Group Testing Algorithm to Determine the Number of Defectives
2020
Scandinavian Workshop on Algorithm Theory
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We study the problem of determining the exact number of defective items in an adaptive group testing by using a minimum number of tests. ...
We improve the existing algorithm and prove a lower bound that shows that the number of tests in our algorithm is optimal up to small additive terms. ...
In this paper, we study the problem of determining exactly the number of defective items with adaptive group testing algorithms. ...
doi:10.4230/lipics.swat.2020.18
dblp:conf/swat/BshoutyHBMNNZ20
fatcat:uowext3ubvbyjo73wwujnrxpxi
Optimal Randomized Group Testing Algorithm to Determine the Number of Defectives
[article]
2020
arXiv
pre-print
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We study the problem of determining exactly the number of defective items in an adaptive Group testing by using a minimum number of tests. ...
We improve the existing algorithm and prove a lower bound that shows that the number of tests in our algorithm is optimal up to small additive terms. ...
In this paper, we study the problem of determining exactly the number of defective items with adaptive Group testing algorithms. ...
arXiv:2001.00441v1
fatcat:d63ivz7p45cn3gb6whw7ejrwem
Group Testing for Efficiently Sampling Hypergraphs When Tests Have Variable Costs
[article]
2020
arXiv
pre-print
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In the group-testing literature, efficient algorithms have been developed to minimize the number of tests required to identify all minimal "defective" sub-groups embedded within a larger group, using deterministic ...
For both algorithms, we show that the optimal initial group size is a function of both the prevalence of defective sets and the positive:negative test cost ratio. ...
Acknowledgment The authors thank Jeffrey S. Buzas and Damin Zhu for helpful discussions regarding group testing algorithms, which ultimately inspired this work. We also thank Paul D.H. ...
arXiv:2010.09205v1
fatcat:fs47tx5atbcdnmyfqvw2zksxzm
Adaptive Group Testing Algorithms to Estimate the Number of Defectives
[article]
2017
arXiv
pre-print
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We study the problem of estimating the number of defective items in adaptive Group testing by using a minimum number of queries. ...
We improve the existing algorithm and prove a lower bound that show that, for constant estimation, the number of tests in our algorithm is optimal. ...
In this paper we study the problem of estimating the number of defective items |I| up to a multiplicative factor of 1 ± ǫ with an adaptive Group testing algorithms. ...
arXiv:1712.00615v1
fatcat:in46r7twmjdvvewa5xmp6wej54
Quantitative estimating size of deep defects in multi-layered structures from eddy current NDT signals using improved ant colony algorithm
2014
Frattura ed Integrità Strutturale
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A novel approach to accurately quantify the two-dimensional axisymmetric deep defect size from eddy current nondestructive testing (NDT) signals is presented here. ...
Detection and quantitative estimation of deep defects in multi-layered structures is an essential task in a range of technological applications, such as maintaining the integrity of structures, enhancing ...
This paper presents an improved ant colony algorithm (IACA) and proposes the use of IACA to quantitative estimate defect size from EC inspection signals. ...
doi:10.3221/igf-esis.28.04
fatcat:2nppwe2hc5fzro56kumuzbuojm
Simple Codes and Sparse Recovery with Fast Decoding
[article]
2019
arXiv
pre-print
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up to K defectives in a population of size N. ...
This decoder can be applied to exact for-all sparse recovery over any field, improving upon previous results with the same number of measurements. ...
Acknowledgments The authors thank Shashanka Ubaru and Thach V. Bui for discussions on the role of the bitmasking technique in sparse recovery. ...
arXiv:1901.02852v2
fatcat:v3fniwgi4nhdvjz4hktm5onawq
Competitive Group Testing and Learning Hidden Vertex Covers with Minimum Adaptivity
[chapter]
2009
Lecture Notes in Computer Science
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Here we explore group testing strategies that use a nearly optimal number of pools and a few stages although d is not known beforehand. ...
The 2-stage strategies still require the knowledge of an upper bound d on the number of defectives, and they guarantee an almost optimal query complexity only relative to this d which can be much larger ...
Acknowledgments This article was inspired by the first author's participation in the wonderful Dagstuhl Seminars 08301 "Group Testing in the Life Sciences" (2008) and 09281 "Search Methodologies" (2009 ...
doi:10.1007/978-3-642-03409-1_9
fatcat:z627dt4foncctmisjtyk7nylhy
Data-driven dynamic decision models
2015
2015 Winter Simulation Conference (WSC)
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We use an efficient model representation and a genetic algorithm-based estimation process to generate simple approximations that explain most of the structure of complex stochastic processes. ...
We also demonstrate the method's ability to recover known data-generating processes by simulating data with agent-based models and correctly deriving the underlying decision models for multiple agent models ...
ACKNOWLEDGMENTS We gratefully acknowledge the authors of R (R Core Team 2014). This manuscript was prepared using knitr (Xie 2014) . ...
doi:10.1109/wsc.2015.7408381
dblp:conf/wsc/NayG15
fatcat:vvkfas6yxzgt7eanxv6vn72tsq
A roller bearing fault diagnosis method using interval support vector deterministic optimization based on nested PSO
2018
Journal of Vibroengineering
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Thus, the nested particle swarm optimization (PSO) based on dynamic decreasing inertia weight is applied to select the optimal Lagrange multiplier vector of this model. ...
An interval support vector deterministic optimization model (ISVD) is proposed for the fault classification problem of uncertainty samples in this paper. ...
Of course, the PSO algorithm needs more iteration to reach the global optimal, and it is more likely not to find the global optimal. ...
doi:10.21595/jve.2018.19613
fatcat:llohabturvcglfz2gssdrpehzu
A new competitive algorithm for group testing
1992
[Proceedings] IEEE INFOCOM '92: The Conference on Computer Communications
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number of tests required by an optimal algorithm when the number of defective items is known in advance. ...
Algorithms for the group testing problem when there is no a priori information on the number of defective items are considered. ...
Acknowledgments We would like to thank Moshe Sidi for valuable discussions. ...
doi:10.1109/infcom.1992.263516
dblp:conf/infocom/Bar-NoyKKH92
fatcat:344fn26djrcvzmv2sr3orqbhum
Two New Perspectives on Multi-Stage Group Testing
2013
Algorithmica
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The group testing problem asks to find d n defective elements out of n elements, by testing subsets (pools) for the presence of defectives. ...
In the strict model of group testing, the goal is to identify all defectives if at most d defectives exist, and otherwise to report that more than d defectives are present. ...
The first author also received support from RWTH Aachen during a visit in 2011. We thank the referees of ICALP2001GT and of this Special Issue for their careful remarks and suggestions. ...
doi:10.1007/s00453-013-9781-4
fatcat:7zzjjcoy5fcxbglfnhwaecrfry
Combinatorial Pair Testing: Distinguishing Workers from Slackers
[chapter]
2013
Lecture Notes in Computer Science
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We give efficient adaptive and nonadaptive CPT algorithms and we show that our methods use an optimal number of testing rounds to within constant factors. ...
We formalize a problem we call combinatorial pair testing (CPT), which has applications to the identification of uncooperative or unproductive participants in pair programming, massively distributed computing ...
This research was supported in part by the National Science Foundation under grants 1011840, 1217322, and 1228639, and by the Office of Naval Research under MURI grant N00014-08-1-1015. ...
doi:10.1007/978-3-642-40104-6_28
fatcat:spz27kqu7featof2xu55yu3z6i
Group-Testing on Hypergraphs with Variable-Cost Tests: A Power Systems Case Study
[article]
2019
arXiv
pre-print
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Thus, the relative speed of each algorithm depends on the relative cost of defective vs. non defective tests, a factor not previously considered in the group-testing literature. ...
We compare RC to a proposed new alternative group-testing algorithm (SIGHT). ...
Acknowledgment The authors thank Jeffrey S. Buzas and Damin Zhu for helpful discussions regarding group testing algorithms, which ultimately inspired the SIGHT algorithm. We also thank Paul D.H. ...
arXiv:1909.04513v1
fatcat:pngqjspc35bzfkto2c3apsbba4
Page 5073 of Mathematical Reviews Vol. , Issue 911
[page]
1991
Mathematical Reviews
Preserved Fulltext
The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
The problem is to classify all items, or find all the defectives with a minimum expected number of tests E(n, p). ...
K. (1-BELL)
On optimal nested group testing algorithms.
J. Statist. Plann. Inference 24 (1990), no. 2, 167-175. ...
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