Christoforos Anagnostopoulos
Title
Cited by
Cited by
Year
Estimating time-varying brain connectivity networks from functional MRI time series
RP Monti, P Hellyer, D Sharp, R Leech, C Anagnostopoulos, G Montana
NeuroImage 103, 427-443, 2014
1442014
Estimating time-varying brain connectivity networks from functional MRI time series
RP Monti, P Hellyer, D Sharp, R Leech, C Anagnostopoulos, G Montana
NeuroImage 103, 427-443, 2014
1442014
When is the area under the receiver operating characteristic curve an appropriate measure of classifier performance?
DJ Hand, C Anagnostopoulos
Pattern Recognition Letters 34 (5), 492-495, 2013
762013
The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI
R Lorenz, RP Monti, IR Violante, C Anagnostopoulos, AA Faisal, ...
NeuroImage 129, 320-334, 2016
632016
A better Beta for the H measure of classification performance
DJ Hand, C Anagnostopoulos
Pattern Recognition Letters 40, 41-46, 2014
632014
Online linear and quadratic discriminant analysis with adaptive forgetting for streaming classification
C Anagnostopoulos, DK Tasoulis, NM Adams, NG Pavlidis, DJ Hand
Statistical Analysis and Data Mining: The ASA Data Science Journal 5 (2 …, 2012
562012
Temporally-adaptive linear classification for handling population drift in credit scoring
NM Adams, DK Tasoulis, C Anagnostopoulos, DJ Hand
Proceedings of COMPSTAT'2010, 167-176, 2010
292010
Financial time series modeling using the Hurst exponent
S Tzouras, C Anagnostopoulos, E McCoy
Physica A: Statistical Mechanics and its Applications 425, 50-68, 2015
222015
Real‐time estimation of dynamic functional connectivity networks
RP Monti, R Lorenz, RM Braga, C Anagnostopoulos, R Leech, G Montana
Human brain mapping 38 (1), 202-220, 2017
212017
Stopping criteria for boosting automatic experimental design using real-time fMRI with Bayesian optimization
R Lorenz, RP Monti, IR Violante, AA Faisal, C Anagnostopoulos, R Leech, ...
arXiv preprint arXiv:1511.07827, 2015
212015
Temporally adaptive estimation of logistic classifiers on data streams
C Anagnostopoulos, DK Tasoulis, NM Adams, DJ Hand
Advances in data analysis and classification 3 (3), 243-261, 2009
212009
Online optimization for variable selection in data streams.
C Anagnostopoulos, DK Tasoulis, DJ Hand, NM Adams
ECAI, 132-136, 2008
192008
A statistical framework for streaming data analysis
C Anagnostopoulos
Imperial College London, 2010
162010
Deciding what to observe next: adaptive variable selection for regression in multivariate data streams
C Anagnostopoulos, NM Adams, DJ Hand
Proceedings of the 2008 ACM symposium on Applied computing, 961-965, 2008
152008
Learning population and subject-specific brain connectivity networks via mixed neighborhood selection
RP Monti, C Anagnostopoulos, G Montana
The Annals of Applied Statistics, 2142-2164, 2017
142017
Measuring classification performance: the hmeasure package.
C Anagnostopoulos
UFIL: http://llcran. r-project. orglweblpackageslhmea-surelvignetteslhmeasurepdf, 2012
142012
Towards tailoring non-invasive brain stimulation using real-time fMRI and Bayesian optimization
R Lorenz, RP Monti, A Hampshire, Y Koush, C Anagnostopoulos, ...
2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI), 1-4, 2016
122016
Graph embeddings of dynamic functional connectivity reveal discriminative patterns of task engagement in HCP data
R Monti, R Lorenz, P Hellyer, R Leech, C Anagnostopoulos, G Montana
2015 International Workshop on Pattern Recognition in NeuroImaging, 1-4, 2015
112015
Information-theoretic data discarding for dynamic trees on data streams
C Anagnostopoulos, RB Gramacy
Entropy 15 (12), 5510-5535, 2013
92013
When Does Active Learning Work?
LPG Evans, NM Adams, C Anagnostopoulos
International Symposium on Intelligent Data Analysis, 174-185, 2013
92013
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