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Idris A. Eckley
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2020 – today
- 2024
- [j29]Alexander Tristan Maximilian Fisch, Daniel Grose, Idris A. Eckley, Paul Fearnhead, Lawrence Bardwell:
anomaly: Detection of Anomalous Structure in Time Series Data. J. Stat. Softw. 110(1) (2024) - [j28]Kes Ward, Gaetano Romano
, Idris A. Eckley
A constant-per-iteration likelihood ratio test for online changepoint detection for exponential family models. Stat. Comput. 34(3): 99 (2024) - [j27]Ziyang Yang, Idris A. Eckley, Paul Fearnhead:
A communication-efficient, online changepoint detection method for monitoring distributed sensor networks. Stat. Comput. 34(3): 115 (2024) - [j26]Gaetano Romano
A Log-Linear Nonparametric Online Changepoint Detection Algorithm Based on Functional Pruning. IEEE Trans. Signal Process. 72: 594-606 (2024) - 2023
- [j25]Edward Austin
Online non-parametric changepoint detection with application to monitoring operational performance of network devices. Comput. Stat. Data Anal. 177: 107551 (2023) - [j24]Gaetano Romano
Fast Online Changepoint Detection via Functional Pruning CUSUM Statistics. J. Mach. Learn. Res. 24: 81:1-81:36 (2023) - [j23]Gaurav Agarwal
Semiparametric detection of changepoints in location, scale, and copula. Stat. Anal. Data Min. 16(5): 456-473 (2023) - 2022
- [j22]Alexander Tristan Maximilian Fisch, Idris A. Eckley
Subset Multivariate Collective and Point Anomaly Detection. J. Comput. Graph. Stat. 31(1): 574-585 (2022) - [j21]Nicholas J. P. Race, Idris A. Eckley, Ajith Kumar Parlikad, Charalampos Rotsos, Ning Wang, Robert J. Piechocki, Philip Stiles, Arjun Parekh, Trevor Burbridge, Peter Willis, Stephen A. Cassidy:
Industry-Academia Research toward Future Network Intelligence: The NG-CDI Prosperity Partnership. IEEE Netw. 36(1): 18-24 (2022) - [j20]Alexander Tristan Maximilian Fisch, Lawrence Bardwell, Idris A. Eckley
Real time anomaly detection and categorisation. Stat. Comput. 32(4): 55 (2022) - [j19]Alexander Tristan Maximilian Fisch, Idris A. Eckley
A linear time method for the detection of collective and point anomalies. Stat. Anal. Data Min. 15(4): 494-508 (2022) - [j18]Alexander Tristan Maximilian Fisch
Innovative and Additive Outlier Robust Kalman Filtering With a Robust Particle Filter. IEEE Trans. Signal Process. 70: 47-56 (2022) - 2021
- [j17]Rebecca E. Wilson, Idris A. Eckley
A wavelet-based approach for imputation in nonstationary multivariate time series. Stat. Comput. 31(2): 18 (2021) - 2020
- [j16]Georg Hahn
BayesProject: Fast computation of a projection direction for multivariate changepoint detection. Stat. Comput. 30(6): 1691-1705 (2020)
2010 – 2019
- 2019
- [j15]Rebecca E. Wilson, Idris A. Eckley
Dynamic detection of anomalous regions within distributed acoustic sensing data streams using locally stationary wavelet time series. Data Min. Knowl. Discov. 33(3): 748-772 (2019) - [j14]David P. Hofmeyr, Nicos G. Pavlidis
Minimum spectral connectivity projection pursuit - Divisive clustering using optimal projections for spectral clustering. Stat. Comput. 29(2): 391-414 (2019) - [j13]Lawrence Bardwell, Paul Fearnhead
Most Recent Changepoint Detection in Panel Data. Technometrics 61(1): 88-98 (2019) - [i3]Hankui Peng, Nicos G. Pavlidis, Idris A. Eckley, Ioannis Tsalamanis:
Subspace Clustering of Very Sparse High-Dimensional Data. CoRR abs/1901.09108 (2019) - 2018
- [j12]Matthew Ludkin
Dynamic stochastic block models: parameter estimation and detection of changes in community structure. Stat. Comput. 28(6): 1201-1213 (2018) - [j11]Timothy Park, Idris A. Eckley
Dynamic classification using multivariate locally stationary wavelet processes. Signal Process. 152: 118-129 (2018) - [c4]Hankui Peng, Nicos G. Pavlidis, Idris A. Eckley, Ioannis Tsalamanis:
Subspace Clustering of Very Sparse High-Dimensional Data. IEEE BigData 2018: 3780-3783 - [i2]Alexander Tristan Maximilian Fisch, Idris Arthur Eckley
A linear time method for the detection of point and collective anomalies. CoRR abs/1806.01947 (2018) - 2017
- [j10]Sarah L. Taylor, Idris A. Eckley
Multivariate locally stationary 2D wavelet processes with application to colour texture analysis. Stat. Comput. 27(4): 1129-1143 (2017) - [j9]Kaylea Haynes, Paul Fearnhead
A computationally efficient nonparametric approach for changepoint detection. Stat. Comput. 27(5): 1293-1305 (2017) - 2016
- [j8]David P. Hofmeyr, Nicos G. Pavlidis
Divisive clustering of high dimensional data streams. Stat. Comput. 26(5): 1101-1120 (2016) - 2015
- [j7]Christopher F. H. Nam, John A. D. Aston, Idris A. Eckley
The Uncertainty of Storm Season Changes: Quantifying the Uncertainty of Autocovariance Changepoints. Technometrics 57(2): 194-206 (2015) - [i1]David P. Hofmeyr, Nicos G. Pavlidis, Idris A. Eckley:
Minimum Spectral Connectivity Projection Pursuit for Unsupervised Classification. CoRR abs/1509.01546 (2015) - 2014
- [j6]Matthew A. Nunes, Sarah L. Taylor, Idris A. Eckley:
A Multiscale Test of Spatial Stationarity for Textured Images in R. R J. 6(1): 20 (2014) - [j5]Sarah L. Taylor, Idris A. Eckley
A Test of Stationarity for Textured Images. Technometrics 56(3): 291-301 (2014) - [j4]Timothy Park, Idris A. Eckley
Estimating Time-Evolving Partial Coherence Between Signals via Multivariate Locally Stationary Wavelet Processes. IEEE Trans. Signal Process. 62(20): 5240-5250 (2014) - 2013
- [j3]Aimee N. Gott, Idris A. Eckley:
A Note on the Effect of Wavelet Choice on the Estimation of the Evolutionary Wavelet Spectrum. Commun. Stat. Simul. Comput. 42(2): 393-406 (2013) - [c3]Rhian Davies
The effect of recovery algorithms on compressive sensing background subtraction. SDF 2013: 1-6
2000 – 2009
- 2005
- [j2]Idris A. Eckley
Efficient computation of the discrete autocorrelation wavelet inner product matrix. Stat. Comput. 15(2): 83-92 (2005) - 2004
- [j1]Ross A. McDonald, David J. Hand
A Multiclass Extension To The Brownboost Algorithm. Int. J. Pattern Recognit. Artif. Intell. 18(5): 905-931 (2004) - [c2]Ross A. McDonald, Idris A. Eckley, David J. Hand:
A Classifier Combination Tree Algorithm. SSPR/SPR 2004: 609-617 - 2003
- [c1]Ross A. McDonald, David J. Hand, Idris A. Eckley:
An Empirical Comparison of Three Boosting Algorithms on Real Data Sets with Artificial Class Noise. Multiple Classifier Systems 2003: 35-44
Coauthor Index
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