Anthony J. Bagnall

130 papers A* 6A 4B 10C 8Misc 1Journal 68Unranked 26

Year	Rank	Type	Title / Venue / Authors
2026	—	`ed.`	Advanced Analytics and Learning on Temporal Data - 10th ECML PKDD Workshop, AALTD 2025, Porto, Portugal, September 19, 2025, Revised Selected Papers AALTD@ECML/PKDD Vincent Lemaire, Georgiana Ifrim, Anthony J. Bagnall, Simon Malinowski, Patrick Schäfer, Romain Tavenard
2026	J	`jnl`	Rock the KASBA: blazingly fast and accurate time series clustering. Data Min. Knowl. Discov. Christopher Holder, Anthony J. Bagnall
2026	J	`jnl`	The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classification. CoRR Matthew Middlehurst, Aiden Rushbrooke, Ali Ismail-Fawaz, Maxime Devanne, Germain Forestier, Angus Dempster, Geoffrey I. Webb, Christopher Holder, Anthony J. Bagnall
2025	—	`ed.`	Advanced Analytics and Learning on Temporal Data - 9th ECML PKDD Workshop, AALTD 2024, Vilnius, Lithuania, September 9-13, 2024, Revised Selected Papers AALTD@ECML/PKDD Vincent Lemaire, Georgiana Ifrim, Anthony J. Bagnall, Thomas Guyet, Simon Malinowski, Patrick Schäfer, Romain Tavenard
2025	—	`conf`	Channel Selection and Creation Algorithms for Electroencephalography Classification with HIVE-COTE. HAIS (2) Aiden Rushbrooke, Matthew Middlehurst, Saber Sami, Anthony J. Bagnall
2025	J	`jnl`	Convolutional- and Deep Learning-Based Techniques for Time Series Ordinal Classification. IEEE Trans. Cybern. Rafael Ayllón-Gavilán, David Guijo-Rubio, Pedro Antonio Gutiérrez, Anthony J. Bagnall, César Hervás-Martínez
2025	—	`conf`	Time Series Machine Learning with Aeon: Classification and Regression. ECML/PKDD (10) Matthew Middlehurst, Anthony J. Bagnall, Germain Forestier, Ali Ismail-Fawaz, Antoine Guillaume
2025	—	`conf`	e-SMOTE: A Train Set Rebalancing Algorithm for Time Series Classification. AALTD@ECML/PKDD Chuanhang Qiu, Matthew Middlehurst, Christopher Holder, Anthony J. Bagnall
2024	A*	`conf`	A Hands-on Introduction to Time Series Classification and Regression. KDD Anthony J. Bagnall, Matthew Middlehurst, Germain Forestier, Ali Ismail-Fawaz, Antoine Guillaume, David Guijo-Rubio, Chang Wei Tan, Angus Dempster, Geoffrey I. Webb
2024	J	`jnl`	A review and evaluation of elastic distance functions for time series clustering. Knowl. Inf. Syst. Christopher Holder, Matthew Middlehurst, Anthony J. Bagnall
2024	J	`jnl`	Bake off redux: a review and experimental evaluation of recent time series classification algorithms. Data Min. Knowl. Discov. Matthew Middlehurst, Patrick Schäfer, Anthony J. Bagnall
2024	J	`jnl`	Correction: Bake off redux: a review and experimental evaluation of recent time series classification algorithms. Data Min. Knowl. Discov. Matthew Middlehurst, Patrick Schäfer, Anthony J. Bagnall
2024	J	`jnl`	On time series clustering with k-means. CoRR Christopher Holder, Anthony J. Bagnall, Jason Lines
2024	J	`jnl`	Rock the KASBA: Blazingly Fast and Accurate Time Series Clustering. CoRR Christopher Holder, Anthony J. Bagnall
2024	J	`jnl`	Unsupervised feature based algorithms for time series extrinsic regression. Data Min. Knowl. Discov. David Guijo-Rubio, Matthew Middlehurst, Guilherme Arcencio, Diego Furtado Silva, Anthony J. Bagnall
2024	J	`jnl`	aeon: a Python Toolkit for Learning from Time Series. J. Mach. Learn. Res. Matthew Middlehurst, Ali Ismail-Fawaz, Antoine Guillaume, Christopher Holder, David Guijo-Rubio, Guzal Bulatova, Leonidas Tsaprounis, Lukasz Mentel, Martin Walter, Patrick Schäfer, Anthony J. Bagnall
2024	J	`jnl`	aeon: a Python toolkit for learning from time series. CoRR Matthew Middlehurst, Ali Ismail-Fawaz, Antoine Guillaume, Christopher Holder, David Guijo-Rubio, Guzal Bulatova, Leonidas Tsaprounis, Lukasz Mentel, Martin Walter, Patrick Schäfer, Anthony J. Bagnall
2023	—	`ed.`	Advanced Analytics and Learning on Temporal Data - 7th ECML PKDD Workshop, AALTD 2022, Grenoble, France, September 19-23, 2022, Revised Selected Papers AALTD@ECML/PKDD Thomas Guyet, Georgiana Ifrim, Simon Malinowski, Anthony J. Bagnall, Patrick Schäfer, Vincent Lemaire
2023	—	`ed.`	Advanced Analytics and Learning on Temporal Data - 8th ECML PKDD Workshop, AALTD 2023, Turin, Italy, September 18-22, 2023, Revised Selected Papers AALTD@ECML/PKDD Georgiana Ifrim, Romain Tavenard, Anthony J. Bagnall, Patrick Schäfer, Simon Malinowski, Thomas Guyet, Vincent Lemaire
2023	J	`jnl`	Bake off redux: a review and experimental evaluation of recent time series classification algorithms. CoRR Matthew Middlehurst, Patrick Schäfer, Anthony J. Bagnall
2023	—	`conf`	Barycentre Averaging for the Move-Split-Merge Time Series Distance Measure. KDIR Christopher Holder, David Guijo-Rubio, Anthony J. Bagnall
2023	—	`conf`	Clustering Time Series with k-Medoids Based Algorithms. AALTD@ECML/PKDD Christopher Holder, David Guijo-Rubio, Anthony J. Bagnall
2023	J	`jnl`	Convolutional and Deep Learning based techniques for Time Series Ordinal Classification. CoRR Rafael Ayllón-Gavilán, David Guijo-Rubio, Pedro Antonio Gutiérrez, Anthony J. Bagnall, César Hervás-Martínez
2023	—	`conf`	Extracting Features from Random Subseries: A Hybrid Pipeline for Time Series Classification and Extrinsic Regression. AALTD@ECML/PKDD Matthew Middlehurst, Anthony J. Bagnall
2023	—	`conf`	Human Activity Segmentation Challenge @ ECML/PKDD'23. AALTD@ECML/PKDD Arik Ermshaus, Patrick Schäfer, Anthony J. Bagnall, Thomas Guyet, Georgiana Ifrim, Vincent Lemaire, Ulf Leser, Colin Leverger, Simon Malinowski
2023	—	`conf`	Time Series Classification of Electroencephalography Data. IWANN (1) Aiden Rushbrooke, Jordan Tsigarides, Saber Sami, Anthony J. Bagnall
2023	J	`jnl`	Unsupervised Feature Based Algorithms for Time Series Extrinsic Regression. CoRR David Guijo-Rubio, Matthew Middlehurst, Guilherme Arcencio, Diego Furtado Silva, Anthony J. Bagnall
2022	J	`jnl`	A Review and Evaluation of Elastic Distance Functions for Time Series Clustering. CoRR Christopher Holder, Matthew Middlehurst, Anthony J. Bagnall
2022	—	`conf`	Dimension Selection Strategies for Multivariate Time Series Classification with HIVE-COTEv2.0. AALTD@ECML/PKDD Alejandro Pasos Ruiz, Anthony J. Bagnall
2022	—	`conf`	The FreshPRINCE: A Simple Transformation Based Pipeline Time Series Classifier. ICPRAI (2) Matthew Middlehurst, Anthony J. Bagnall
2022	J	`jnl`	The FreshPRINCE: A Simple Transformation Based Pipeline Time Series Classifier. CoRR Matthew Middlehurst, Anthony J. Bagnall
2021	—	`ed.`	Advanced Analytics and Learning on Temporal Data - 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised Selected Papers AALTD@ECML/PKDD Vincent Lemaire, Simon Malinowski, Anthony J. Bagnall, Thomas Guyet, Romain Tavenard, Georgiana Ifrim
2021	J	`jnl`	HIVE-COTE 2.0: a new meta ensemble for time series classification. CoRR Matthew Middlehurst, James Large, Michael Flynn, Jason Lines, Aaron Bostrom, Anthony J. Bagnall
2021	J	`jnl`	HIVE-COTE 2.0: a new meta ensemble for time series classification. Mach. Learn. Matthew Middlehurst, James Large, Michael Flynn, Jason Lines, Aaron Bostrom, Anthony J. Bagnall
2021	J	`jnl`	The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification. CoRR Matthew Middlehurst, James Large, Gavin C. Cawley, Anthony J. Bagnall
2021	J	`jnl`	The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Min. Knowl. Discov. Alejandro Pasos Ruiz, Michael Flynn, James Large, Matthew Middlehurst, Anthony J. Bagnall
2020	J	`jnl`	A tale of two toolkits, report the third: on the usage and performance of HIVE-COTE v1.0. CoRR Anthony J. Bagnall, Michael Flynn, James Large, Jason Lines, Matthew Middlehurst
2020	—	`ed.`	Advanced Analytics and Learning on Temporal Data - 4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers AALTD@PKDD/ECML Vincent Lemaire, Simon Malinowski, Anthony J. Bagnall, Alexis Bondu, Thomas Guyet, Romain Tavenard
2020	—	`ed.`	Advanced Analytics and Learning on Temporal Data - 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers AALTD@PKDD/ECML Vincent Lemaire, Simon Malinowski, Anthony J. Bagnall, Thomas Guyet, Romain Tavenard, Georgiana Ifrim
2020	J	`jnl`	An ultra-fast time series distance measure to allow data mining in more complex real-world deployments. Data Min. Knowl. Discov. Shaghayegh Gharghabi, Shima Imani, Anthony J. Bagnall, Amirali Darvishzadeh, Eamonn J. Keogh
2020	J	`jnl`	Benchmarking Multivariate Time Series Classification Algorithms. CoRR Alejandro Pasos Ruiz, Michael Flynn, Anthony J. Bagnall
2020	J	`jnl`	Detecting Electric Devices in 3D Images of Bags. CoRR Anthony J. Bagnall, Paul Southam, James Large, Richard W. Harvey
2020	—	`conf`	Developing Ensemble Methods for Detecting Anomalies in Water Level Data. SGAI Conf. Thakolpat Khampuengson, Anthony J. Bagnall, Wenjia Wang
2020	—	`conf`	On the Usage and Performance of the Hierarchical Vote Collective of Transformation-Based Ensembles Version 1.0 (HIVE-COTE v1.0). AALTD@PKDD/ECML Anthony J. Bagnall, Michael Flynn, James Large, Jason Lines, Matthew Middlehurst
2020	—	`conf`	Ordinal Versus Nominal Time Series Classification. AALTD@PKDD/ECML David Guijo-Rubio, Pedro Antonio Gutiérrez, Anthony J. Bagnall, César Hervás-Martínez
2020	—	`conf`	The Canonical Interval Forest (CIF) Classifier for Time Series Classification. IEEE BigData Matthew Middlehurst, James Large, Anthony J. Bagnall
2020	J	`jnl`	The Canonical Interval Forest (CIF) Classifier for Time Series Classification. CoRR Matthew Middlehurst, James Large, Anthony J. Bagnall
2020	—	`conf`	The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification. ECML/PKDD (1) Matthew Middlehurst, James Large, Gavin C. Cawley, Anthony J. Bagnall
2020	B	`conf`	Time series ordinal classification via shapelets. IJCNN David Guijo-Rubio, Pedro Antonio Gutiérrez, Anthony J. Bagnall, César Hervás-Martínez
2019	—	`conf`	A Hybrid Approach to Time Series Classification with Shapelets. IDEAL (1) David Guijo-Rubio, Pedro Antonio Gutiérrez, Romain Tavenard, Anthony J. Bagnall
2019	J	`jnl`	A probabilistic classifier ensemble weighting scheme based on cross-validated accuracy estimates. Data Min. Knowl. Discov. James Large, Jason Lines, Anthony J. Bagnall
2019	J	`jnl`	A tale of two toolkits, report the first: benchmarking time series classification algorithms for correctness and efficiency. CoRR Anthony J. Bagnall, Franz J. Király, Markus Löning, Matthew Middlehurst, George Oastler
2019	J	`jnl`	A tale of two toolkits, report the second: bake off redux. Chapter 1. dictionary based classifiers. CoRR Anthony J. Bagnall, James Large, Matthew Middlehurst
2019	Misc	`conf`	Can Automated Smoothing Significantly Improve Benchmark Time Series Classification Algorithms? HAIS James Large, Paul Southam, Anthony J. Bagnall
2019	—	`conf`	Classifying Flies Based on Reconstructed Audio Signals. IDEAL (2) Michael Flynn, Anthony J. Bagnall
2019	J	`jnl`	Data Series Management (Dagstuhl Seminar 19282). Dagstuhl Reports Anthony J. Bagnall, Richard L. Cole, Themis Palpanas, Konstantinos Zoumpatianos
2019	—	`conf`	Mixing Hetero- and Homogeneous Models in Weighted Ensembles. IDEAL (1) James Large, Anthony J. Bagnall
2019	J	`jnl`	On time series classification with dictionary-based classifiers. Intell. Data Anal. James Large, Anthony J. Bagnall, Simon Malinowski, Romain Tavenard
2019	—	`conf`	Scalable Dictionary Classifiers for Time Series Classification. IDEAL (1) Matthew Middlehurst, William Vickers, Anthony J. Bagnall
2019	J	`jnl`	Scalable Dictionary Classifiers for Time Series Classification. CoRR Matthew Middlehurst, William Vickers, Anthony J. Bagnall
2019	J	`jnl`	The UCR time series archive. IEEE CAA J. Autom. Sinica Hoang Anh Dau, Anthony J. Bagnall, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana, Eamonn J. Keogh
2019	J	`jnl`	sktime: A Unified Interface for Machine Learning with Time Series. CoRR Markus Löning, Anthony J. Bagnall, Sajaysurya Ganesh, Viktor Kazakov, Jason Lines, Franz J. Király
2018	J	`jnl`	Can automated smoothing significantly improve benchmark time series classification algorithms? CoRR James Large, Paul Southam, Anthony J. Bagnall
2018	—	`conf`	Detecting Forged Alcohol Non-invasively Through Vibrational Spectroscopy and Machine Learning. PAKDD (1) James Large, E. Kate Kemsley, Nikolaus Wellner, Ian Goodall, Anthony J. Bagnall
2018	J	`jnl`	From BOP to BOSS and Beyond: Time Series Classification with Dictionary Based Classifiers. CoRR James Large, Anthony J. Bagnall, Simon Malinowski, Romain Tavenard
2018	J	`jnl`	Is rotation forest the best classifier for problems with continuous features? CoRR Anthony J. Bagnall, Aaron Bostrom, Gavin C. Cawley, Michael Flynn, James Large, Jason Lines
2018	A*	`conf`	Matrix Profile XII: MPdist: A Novel Time Series Distance Measure to Allow Data Mining in More Challenging Scenarios. ICDM Shaghayegh Gharghabi, Shima Imani, Anthony J. Bagnall, Amirali Darvishzadeh, Eamonn J. Keogh
2018	J	`jnl`	Optimizing dynamic time warping's window width for time series data mining applications. Data Min. Knowl. Discov. Hoang Anh Dau, Diego Furtado Silva, François Petitjean, Germain Forestier, Anthony J. Bagnall, Abdullah Mueen, Eamonn J. Keogh
2018	J	`jnl`	The UCR Time Series Archive. CoRR Hoang Anh Dau, Anthony J. Bagnall, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana, Eamonn J. Keogh
2018	J	`jnl`	The UEA multivariate time series classification archive, 2018. CoRR Anthony J. Bagnall, Hoang Anh Dau, Jason Lines, Michael Flynn, James Large, Aaron Bostrom, Paul Southam, Eamonn J. Keogh
2018	J	`jnl`	Time Series Classification with HIVE-COTE: The Hierarchical Vote Collective of Transformation-Based Ensembles. ACM Trans. Knowl. Discov. Data Jason Lines, Sarah Taylor, Anthony J. Bagnall
2017	J	`jnl`	A Shapelet Transform for Multivariate Time Series Classification. CoRR Aaron Bostrom, Anthony J. Bagnall
2017	J	`jnl`	Binary Shapelet Transform for Multiclass Time Series Classification. Trans. Large Scale Data Knowl. Centered Syst. Aaron Bostrom, Anthony J. Bagnall
2017	—	`conf`	Judicious setting of Dynamic Time Warping's window width allows more accurate classification of time series. IEEE BigData Hoang Anh Dau, Diego Furtado Silva, François Petitjean, Germain Forestier, Anthony J. Bagnall, Eamonn J. Keogh
2017	J	`jnl`	On the Use of Default Parameter Settings in the Empirical Evaluation of Classification Algorithms. CoRR Anthony J. Bagnall, Gavin C. Cawley
2017	J	`jnl`	Simulated Data Experiments for Time Series Classification Part 1: Accuracy Comparison with Default Settings. CoRR Anthony J. Bagnall, Aaron Bostrom, James Large, Jason Lines
2017	J	`jnl`	The Heterogeneous Ensembles of Standard Classification Algorithms (HESCA): the Whole is Greater than the Sum of its Parts. CoRR James Large, Jason Lines, Anthony J. Bagnall
2017	J	`jnl`	The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Min. Knowl. Discov. Anthony J. Bagnall, Jason Lines, Aaron Bostrom, James Large, Eamonn J. Keogh
2016	J	`jnl`	Ensembles of random sphere cover classifiers. Pattern Recognit. Reda Younsi, Anthony J. Bagnall
2016	A*	`conf`	HIVE-COTE: The Hierarchical Vote Collective of Transformation-Based Ensembles for Time Series Classification. ICDM Jason Lines, Sarah Taylor, Anthony J. Bagnall
2016	J	`jnl`	The Great Time Series Classification Bake Off: An Experimental Evaluation of Recently Proposed Algorithms. Extended Version. CoRR Anthony J. Bagnall, Aaron Bostrom, James Large, Jason Lines
2016	A*	`conf`	Time-series classification with COTE: The collective of transformation-based ensembles. ICDE Anthony J. Bagnall, Jason Lines, Jon Hills, Aaron Bostrom
2015	B	`conf`	Benchmarking the semi-supervised naïve Bayes classifier. IJCNN Awat A. Saeed, Gavin C. Cawley, Anthony J. Bagnall
2015	B	`conf`	Binary Shapelet Transform for Multiclass Time Series Classification. DaWaK Aaron Bostrom, Anthony J. Bagnall
2015	J	`jnl`	Time series classification with ensembles of elastic distance measures. Data Min. Knowl. Discov. Jason Lines, Anthony J. Bagnall
2015	J	`jnl`	Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles. IEEE Trans. Knowl. Data Eng. Anthony J. Bagnall, Jason Lines, Jon Hills, Aaron Bostrom
2014	J	`jnl`	A Run Length Transformation for Discriminating Between Auto Regressive Time Series. J. Classif. Anthony J. Bagnall, Gareth J. Janacek
2014	J	`jnl`	An Experimental Evaluation of Nearest Neighbour Time Series Classification. CoRR Anthony J. Bagnall, Jason Lines
2014	J	`jnl`	Classification of time series by shapelet transformation. Data Min. Knowl. Discov. Jon Hills, Jason Lines, Edgaras Baranauskas, James Mapp, Anthony J. Bagnall
2014	A	`conf`	Ensembles of Elastic Distance Measures for Time Series Classification. SDM Jason Lines, Anthony J. Bagnall
2014	J	`jnl`	Ensembles of Random Sphere Cover Classifiers. CoRR Anthony J. Bagnall, Reda Younsi
2014	J	`jnl`	Finding Motif Sets in Time Series. CoRR Anthony J. Bagnall, Jon Hills, Jason Lines
2014	J	`jnl`	Predictive Modelling of Bone Age through Classification and Regression of Bone Shapes. CoRR Anthony J. Bagnall, Luke M. Davis
2013	J	`jnl`	BruteSuppression: a size reduction method for Apriori rule sets. J. Intell. Inf. Syst. Jon Hills, Anthony J. Bagnall, Beatriz de la Iglesia, Graeme Richards
2013	C	`conf`	Clupea Harengus: Intraspecies Distinction using Curvature Scale Space and Shapelets - Classification of North-sea and Thames Herring using Boundary Contour of Sagittal Otoliths. ICPRAM James Mapp, Mark Fisher, Anthony J. Bagnall, Jason Lines, Sally Warne, Joe Scutt Phillips
2012	A*	`conf`	A shapelet transform for time series classification. KDD Jason Lines, Luke M. Davis, Jon Hills, Anthony J. Bagnall
2012	C	`conf`	Alternative Quality Measures for Time Series Shapelets. IDEAL Jason Lines, Anthony J. Bagnall
2012	J	`jnl`	An efficient randomised sphere cover classifier. Int. J. Data Min. Model. Manag. Reda Younsi, Anthony J. Bagnall
2012	C	`conf`	Automated Bone Age Assessment Using Feature Extraction. IDEAL Luke M. Davis, Barry-John Theobald, Anthony J. Bagnall
2012	C	`conf`	Interestingness Measures for Fixed Consequent Rules. IDEAL Jon Hills, Luke M. Davis, Anthony J. Bagnall
2012	J	`jnl`	On the Segmentation and Classification of Hand Radiographs. Int. J. Neural Syst. Luke M. Davis, Barry-John Theobald, Jason Lines, Andoni Toms, Anthony J. Bagnall
2012	A	`conf`	Transformation Based Ensembles for Time Series Classification. SDM Anthony J. Bagnall, Luke M. Davis, Jon Hills, Jason Lines
2011	C	`conf`	Classification of Household Devices by Electricity Usage Profiles. IDEAL Jason Lines, Anthony J. Bagnall, Patrick Caiger-Smith, Simon Anderson
2011	C	`conf`	On the Extraction and Classification of Hand Outlines. IDEAL Luke M. Davis, Barry-John Theobald, Andoni Toms, Anthony J. Bagnall
2010	C	`conf`	A Randomized Sphere Cover Classifier. IDEAL Reda Younsi, Anthony J. Bagnall
2009	J	`jnl`	A learning classifier system for mazes with aliasing clones. Nat. Comput. Zhanna V. Zatuchna, Anthony J. Bagnall
2009	J	`jnl`	Learning Mazes with Aliasing States: An LCS Algorithm with Associative Perception. Adapt. Behav. Zhanna V. Zatuchna, Anthony J. Bagnall
2008	—	`conf`	Time Series Data Mining Algorithms for Identifying Short RNA in Arabidopsis thaliana. BIOCOMP Anthony J. Bagnall, Simon Moxon, David J. Studholme, Vincent Moulton
2007	—	`conf`	Adaptive Sniping for Volatile and Stable Continuous Double Auction Markets. AMEC/TADA Iain Toft, Anthony J. Bagnall
2007	J	`jnl`	Learning Classifier System Ensembles With Rule-Sharing. IEEE Trans. Evol. Comput. Larry Bull, Matthew Studley, Anthony J. Bagnall, Ian M. Whittley
2007	J	`jnl`	Super Computer Heterogeneous Classifier Meta-Ensembles. Int. J. Data Warehous. Min. Anthony J. Bagnall, Gavin C. Cawley, Ian M. Whittley, Larry Bull, Matthew Studley, Mike Pettipher, Firat Tekiner
2006	J	`jnl`	A Bit Level Representation for Time Series Data Mining with Shape Based Similarity. Data Min. Knowl. Discov. Anthony J. Bagnall, Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh, Stefano Lonardi, Gareth J. Janacek
2006	—	`conf`	A Comparison of DWT/PAA and DFT for Time Series Classification. DMIN Anthony J. Bagnall, Ian M. Whittley, Gareth J. Janacek, Kate Kemsley, Matthew Studley, Larry Bull
2006	J	`jnl`	Autonomous Adaptive Agents for Single Seller Sealed Bid Auctions. Auton. Agents Multi Agent Syst. Anthony J. Bagnall, Iain Toft
2006	B	`conf`	Variance Stabilizing Regression Ensembles for Environmental Models. IJCNN Anthony J. Bagnall, Ian M. Whittley, Matthew Studley, Mike Pettipher, Firat Tekiner, Larry Bull
2005	B	`conf`	A Likelihood Ratio Distance Measure for the Similarity Between the Fourier Transform of Time Series. PAKDD Gareth J. Janacek, Anthony J. Bagnall, M. Powell
2005	B	`conf`	A Novel Bit Level Time Series Representation with Implication of Similarity Search and Clustering. PAKDD Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh, Anthony J. Bagnall, Stefano Lonardi
2005	J	`jnl`	A multiagent model of the UK market in electricity generation. IEEE Trans. Evol. Comput. Anthony J. Bagnall, George D. Smith
2005	B	`conf`	AgentP classifier system: self-adjusting vs. gradual approach. Congress on Evolutionary Computation Zhanna V. Zatuchna, Anthony J. Bagnall
2005	J	`jnl`	Clustering Time Series with Clipped Data. Mach. Learn. Anthony J. Bagnall, Gareth J. Janacek
2005	B	`conf`	On the use of rule-sharing in learning classifier system ensembles. Congress on Evolutionary Computation Larry Bull, Matthew Studley, Anthony J. Bagnall, Ian M. Whittley
2004	A*	`conf`	Clustering time series from ARMA models with clipped data. KDD Anthony J. Bagnall, Gareth J. Janacek
2004	C	`conf`	Improving Decision Tree Performance Through Induction- and Cluster-Based Stratified Sampling. IDEAL Abdul Aziz Gill, George D. Smith, Anthony J. Bagnall
2003	—	`conf`	An Agent Model for First Price and Second Price Private Value Auctions. Artificial Evolution Anthony J. Bagnall, Iain Toft
2003	B	`conf`	Data mining rules using multi-objective evolutionary algorithms. IEEE Congress on Evolutionary Computation Beatriz de la Iglesia, M. S. Philpott, Anthony J. Bagnall, Victor J. Rayward-Smith
2003	B	`conf`	Learning classifier systems for data mining: a comparison of XCS with other classifiers for the Forest Cover data set. IJCNN Anthony J. Bagnall, Gavin C. Cawley
2001	J	`jnl`	The next release problem. Inf. Softw. Technol. Anthony J. Bagnall, Victor J. Rayward-Smith, Ian M. Whittley
2000	A	`conf`	A Multi-Adaptive Agent Model of Generator Bidding in the UK Market in Electricity. GECCO Anthony J. Bagnall
1999	A	`conf`	Using an Adaptive Agent to Bid in a Simplified Model of the UK Market in Electricity. GECCO Anthony J. Bagnall, George D. Smith
1997	—	`conf`	The Cryptanalysis of a Three Rotor Machine Using a Genetic Algorithm. ICGA Anthony J. Bagnall, Geoff P. McKeown, Victor J. Rayward-Smith