Seuraa
Oliver Johnson
Oliver Johnson
Professor of Information Theory, School of Mathematics, University of Bristol, UK
Vahvistettu sähköpostiosoite verkkotunnuksessa bristol.ac.uk - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Information theory and the central limit theorem
OT Johnson
World Scientific, 2004
3442004
Group testing: an information theory perspective
M Aldridge, O Johnson, J Scarlett
Foundations and Trends in Communications and Information Theory 15 (3-4 …, 2019
2062019
Fisher information inequalities and the central limit theorem
O Johnson, A Barron
Probability Theory and Related Fields 129 (3), 391-409, 2004
1582004
Group testing algorithms: Bounds and simulations
M Aldridge, L Baldassini, O Johnson
IEEE Transactions on Information Theory 60 (6), 3671-3687, 2014
1482014
The capacity of adaptive group testing
L Baldassini, O Johnson, M Aldridge
2013 IEEE International Symposium on Information Theory (ISIT), 2676-2680, 2013
932013
Some results concerning maximum Rényi entropy distributions
O Johnson, C Vignat
Annales de l'IHP Probabilités et statistiques 43 (3), 339-351, 2007
862007
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
852010
Entropy and the law of small numbers
I Kontoyiannis, P Harremoës, O Johnson
IEEE Transactions on Information Theory 51 (2), 466-472, 2005
752005
Log-concavity and the maximum entropy property of the Poisson distribution
O Johnson
Stochastic Processes and their Applications 117 (6), 791-802, 2007
672007
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
662019
Central limit theorem and convergence to stable laws in Mallows distance
O Johnson, R Samworth
Bernoulli 11 (5), 829-845, 2005
592005
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
492019
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
49*2013
Compound Poisson approximation via information functionals
AD Barbour, O Johnson, I Kontoyiannis, M Madiman
Electronic Journal of Probability 15 (42), 1344-1368, 2010
382010
Preservation of log-concavity on summation
O Johnson, C Goldschmidt
ESAIM: Probability and Statistics 10, 206-215, 2006
382006
Thinning, entropy, and the law of thin numbers
P Harremoës, O Johnson, I Kontoyiannis
IEEE Transactions on Information Theory 56 (9), 4228-4244, 2010
342010
Monotonicity, thinning, and discrete versions of the entropy power inequality
O Johnson, Y Yu
IEEE Transactions on Information Theory 56 (11), 5387-5395, 2010
332010
Thinning and the law of small numbers
P Harremoës, O Johnson, I Kontoyiannis
2007 IEEE International Symposium on Information Theory (ISIT), 1491-1495, 2007
302007
Fisher information, compound Poisson approximation, and the Poisson channel
M Madiman, O Johnson, I Kontoyiannis
2007 IEEE International Symposium on Information Theory (ISIT), 976-980, 2007
292007
Reliability of broadcast communications under sparse random linear network coding
S Brown, O Johnson, A Tassi
IEEE Transactions on Vehicular Technology 67 (5), 4677-4682, 2018
272018
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Artikkelit 1–20