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Oliver Johnson
Oliver Johnson
Professor of Information Theory, School of Mathematics, University of Bristol, UK
在 bristol.ac.uk 的電子郵件地址已通過驗證 - 首頁
標題
引用次數
引用次數
年份
Information theory and the central limit theorem
OT Johnson
World Scientific, 2004
4122004
Group testing: an information theory perspective
M Aldridge, O Johnson, J Scarlett
Foundations and Trends in Communications and Information Theory 15 (3-4 …, 2019
3072019
Group testing algorithms: Bounds and simulations
M Aldridge, L Baldassini, O Johnson
IEEE Transactions on Information Theory 60 (6), 3671-3687, 2014
1852014
Fisher information inequalities and the central limit theorem
O Johnson, A Barron
Probability Theory and Related Fields 129, 391-409, 2004
1822004
The capacity of adaptive group testing
L Baldassini, O Johnson, M Aldridge
2013 IEEE International Symposium on Information Theory (ISIT), 2676-2680, 2013
1102013
Note on noisy group testing: Asymptotic bounds and belief propagation reconstruction
D Sejdinovic, O Johnson
2010 48th Annual Allerton Conference on Communication, Control, and …, 2010
1022010
Some results concerning maximum Rényi entropy distributions
O Johnson, C Vignat
Annales de l'IHP Probabilités et statistiques 43 (3), 339-351, 2007
972007
Encrypted Databases: New Volume Attacks against Range Queries
Z Gui, O Johnson, B Warinschi
Proceedings of the 26th ACM Conference on Computer and Communications …, 2019
952019
Performance of Group Testing Algorithms With Near-Constant Tests Per Item
O Johnson, M Aldridge, J Scarlett
IEEE Transactions on Information Theory 65 (2), 707-723, 2019
852019
Entropy and the law of small numbers
I Kontoyiannis, P Harremoës, O Johnson
IEEE Transactions on Information Theory 51 (2), 466-472, 2005
842005
Log-concavity and the maximum entropy property of the Poisson distribution
O Johnson
Stochastic Processes and their Applications 117 (6), 791-802, 2007
802007
Central limit theorem and convergence to stable laws in Mallows distance
O Johnson, R Samworth
Bernoulli 11 (5), 829-845, 2005
662005
Log-concavity, ultra-log-concavity, and a maximum entropy property of discrete compound Poisson measures
O Johnson, I Kontoyiannis, M Madiman
Discrete Applied Mathematics 161 (9), 1232-1250, 2013
61*2013
Thinning, entropy, and the law of thin numbers
P Harremoës, O Johnson, I Kontoyiannis
IEEE Transactions on Information Theory 56 (9), 4228-4244, 2010
432010
Compound Poisson approximation via information functionals
AD Barbour, O Johnson, I Kontoyiannis, M Madiman
Electronic Journal of Probability 15 (42), 1344-1368, 2010
432010
Noisy non-adaptive group testing: A (near-) definite defectives approach
J Scarlett, O Johnson
IEEE Transactions on Information Theory 66 (6), 3775-3797, 2020
412020
Preservation of log-concavity on summation
O Johnson, C Goldschmidt
ESAIM: Probability and Statistics 10, 206-215, 2006
402006
Thinning and the law of small numbers
P Harremoës, O Johnson, I Kontoyiannis
2007 IEEE International Symposium on Information Theory (ISIT), 1491-1495, 2007
372007
The COVID-19 pandemic as experienced by the individual
P Garland, D Babbitt, M Bondarenko, A Sorichetta, AJ Tatem, O Johnson
arXiv preprint arXiv:2005.01167, 2020
35*2020
Monotonicity, thinning, and discrete versions of the entropy power inequality
O Johnson, Y Yu
IEEE Transactions on Information Theory 56 (11), 5387-5395, 2010
352010
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