Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Andrew B. Gardner"'
Publikováno v:
Information Systems. 80:124-135
We present a novel strategy for approximate furthest neighbor search that selects a set of candidate points using the data distribution. This strategy leads to an algorithm, which we call DrusillaSelect , that is able to outperform existing approxima
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1006edc6bbfbf646cde593559ab07538
https://doi.org/10.1016/j.is.2017.12.010
https://doi.org/10.1016/j.is.2017.12.010
Autor:
Slawomir Grzonkowski, Javier Echauz, Saurabh Shintre, Sarfaraz Hussein, Andrew B. Gardner, Jay Dhaliwal, Keith Kenemer
Publikováno v:
Annual Conference of the PHM Society. 11
Machine learning models are vulnerable to adversarial inputs that induce seemingly unjustifiable errors. As automated classifiers are increasingly used in industrial control systems and machinery, these adversarial errors could grow to be a serious p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6678a9bd6bd0815d2c9babb88030fef
https://doi.org/10.36001/phmconf.2019.v11i1.865
https://doi.org/10.36001/phmconf.2019.v11i1.865
Autor:
Alexey Kleymenov, Alejandro Mosquera, Ryan R. Curtin, Slawomir Grzonkowski, Andrew B. Gardner
Publikováno v:
ARES
Modern malware typically makes use of a domain generation algorithm (DGA) to avoid command and control domains or IPs being seized or sinkholed. This means that an infected system may attempt to access many domains in an attempt to contact the comman
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1fcd69e3c4afb0180fd35bc8ed60aec9
http://arxiv.org/abs/1810.02023
http://arxiv.org/abs/1810.02023
Autor:
Ryan R. Curtin, Andrew B. Gardner
Publikováno v:
Similarity Search and Applications ISBN: 9783319467580
SISAP
SISAP
We present a novel strategy for approximate furthest neighbor search that selects a candidate set using the data distribution. This strategy leads to an algorithm, which we call DrusillaSelect, that is able to outperform existing approximate furthest
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::069ab64bae8fbfd8e938bd7e7cd2e1fb
https://doi.org/10.1007/978-3-319-46759-7_17
https://doi.org/10.1007/978-3-319-46759-7_17
Autor:
Gregory A. Worrell, Beverly K. Sturges, Andrew B. Gardner, W. Douglas Sheffield, Kathryn A. Davis, Kent W. Leyde, Charles H. Vite, Brian Litt, Vanessa Ruedebusch
Publikováno v:
Epilepsy Research. 96:116-122
We present results from continuous intracranial electroencephalographic (iEEG) monitoring in 6 dogs with naturally occurring epilepsy, a disorder similar to the human condition in its clinical presentation, epidemiology, electrophysiology and respons
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f5bb0a045f2dbed7a46f39beab643ba
https://doi.org/10.1016/j.eplepsyres.2011.05.011
https://doi.org/10.1016/j.eplepsyres.2011.05.011
Autor:
Richard W. Marsh, Fredric B. Meyer, Greg Worrell, Sanqing Hu, Steve Goerss, Gregory J. Cascino, S. Matt Stead, Andrew B. Gardner, Brian Litt
Publikováno v:
Brain. 131:928-937
Neuronal oscillations span a wide range of spatial and temporal scales that extend beyond traditional clinical EEG. Recent research suggests that high-frequency oscillations (HFO), in the ripple (80-250 Hz) and fast ripple (250-1000 Hz) frequency ran
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3949be7af8df17b48821ad45e8a58483
https://doi.org/10.1093/brain/awn006
https://doi.org/10.1093/brain/awn006
Publisher Summary Computational neuroscience research in epilepsy encompasses a broad range of scales in space and time. Some of the most promising work in this area focuses on biophysically accurate models of circuits and synapses in brain that give
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a65a7d96c622bb3b027a2a71d78d52d5
https://doi.org/10.1016/b978-012373649-9.50035-1
https://doi.org/10.1016/b978-012373649-9.50035-1
Publikováno v:
Advances in Neural Networks – ISNN 2007 ISBN: 9783540723929
ISNN (2)
ISNN (2)
In [1], we developed two methods to automatically identify the contribution of the recording reference signal from multi-channel intracranial Electroencephalography (iEEG) recordings. In this study, we subtract the reference recording contribution to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9011a03c736478e25991e7afc3b90d9d
https://doi.org/10.1007/978-3-540-72393-6_150
https://doi.org/10.1007/978-3-540-72393-6_150
Autor:
Hiram Firpi, Otis Smart, B. Lift, Javier Echauz, Andrew B. Gardner, George Georgoulas, George Vachtsevanos
Publikováno v:
2007 Mediterranean Conference on Control & Automation.
This paper introduces a framework for addressing neurological disorders and specifically epilepsy. One percent of the world's population is experiencing epileptic seizures a large percentage of which cannot be cured via medication or surgery. Recent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec8e16ae86f6f648128049544d6e57d3
https://doi.org/10.1109/med.2007.4433785
https://doi.org/10.1109/med.2007.4433785
Human and Automated Detection of High-Frequency Oscillations in Clinical Intracranial EEG Recordings
Objective Recent studies indicate that pathologic high-frequency oscillations (HFOs) are signatures of epileptogenic brain. Automated tools are required to characterize these events. We present a new algorithm tuned to detect HFOs from 30 to 85Hz, an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a6ce1b04a71066f98e1d0f5627d54f2e
https://europepmc.org/articles/PMC2020804/
https://europepmc.org/articles/PMC2020804/