Journal papers

2020

  • Hussam Abdelkarim, Matthew Durie, Rinaldo Bellomo, Christoph Bergmeir, Omar Badawi, Khaled El-Khawas, David Pilcher (2020) A comparison of characteristics and outcomes of patients admitted to the ICU with asthma in Australia and New Zealand and United States. In: Journal of Asthma, 57, (4), pp. 398-404 (IF 2.081, Q3 in ``Respiratory System'', JCR 2018). Abstract DOI bib
  • H. Bandara, C. Bergmeir, S. Smyl (2020) Forecasting Across Time Series Databases using Recurrent Neural Networks on Groups of Similar Series: A Clustering Approach. In: Expert Systems with Applications, 140, pp. 112896 (IF 4.292, Q1 in ``Computer Science, Artificial Intelligence'', JCR 2018). Abstract  pdf bib
  • Dilini Rajapaksha, Christoph Bergmeir, Wray Buntine (2020) LoRMIkA: Local rule-based model interpretability with k-optimal associations. In: Information Sciences, 540, pp. 221-241. Abstract DOI  pdf bib
  • Kasun Bandara, Christoph Bergmeir, Hansika Hewamalage (2020) LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series with Multiple Seasonal Patterns. In: IEEE Transactions on Neural Networks and Learning Systems, (forthcoming). Abstract  pdf bib
  • Hansika Hewamalage, Christoph Bergmeir, Kasun Bandara (2020) Recurrent Neural Networks for Time Series Forecasting: Current Status and Future Directions. In: International Journal of Forecasting, (forthcoming). Abstract  pdf bib

2019

  • Diva Baggio, Trisha Peel, Anton Peleg, Sharon Avery, Madhurima Prayaga, Michelle Foo, Gholamreza Haffari, Ming Liu, Christoph Bergmeir, Michelle Ananda-Rajah (2019) Closing the gap in surveillance and audit of invasive mold diseases for antifungal stewardship using machine learning. In: Journal of Clinical Medicine, 8, (9), pp. 1390 (IF 5.688, Q1 in ``Medicine, General & Internal'', JCR 2018). Abstract bib

2018

  • F.J. Baldan, S. Ramirez-Gallego, C. Bergmeir, F. Herrera, J. M. Benitez (2018) A Forecasting Methodology for Workload Forecasting in Cloud Systems. In: IEEE Transactions on Cloud Computing, 6, (4), pp. 929-941 (IF 5.967, top 4% (Q1) in ``Computer Science, Information Systems'', and top 7% (Q1) in ``Computer Science, Theory & Methods'', JCR 2018). Abstract DOI bib
  • C. Bergmeir, R. J. Hyndman, B. Koo (2018) A Note on the Validity of Cross-Validation for Evaluating Autoregressive Time Series Prediction. In: Computational Statistics and Data Analysis, 120, pp. 70-83 (IF 1.323, Q2 ranking in ``Statistics & Probability'', JCR 2018). Abstract DOI bib
  • Shane Nanayakkara, Sam Fogarty, Michael Tremeer, Kelvin Ross, Brent Richards, Christoph Bergmeir, Sheng Xu, Dion Stub, Karen Smith, Mark Tacey, Danny Liew, David Pilcher, David M Kaye (2018) Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study. In: PLoS Medicine, 15 (11): e1002709, pp. 1-16 (IF 11.048, top 5% (Q1) in ``Medicine, General & Internal'', JCR 2018). Abstract DOI bib
  • Fotios Petropoulos, Rob J Hyndman, Christoph Bergmeir (2018) Exploring the sources of uncertainty: why does bagging for time series forecasting work?. In: European Journal of Operational Research, 268, pp. 545-554 (IF 3.806, Q1 in ``Operations Research & Management Sciences'', JCR 2018). Abstract bib
  • Daniel Peralta, Christoph Bergmeir, Martin Krone, Marta Galende, Manuel Menendez, Gregorio I Sainz-Palmero, Carlos Martinez Beltrand, Frank Klawonn, Jose M Benitez (2018) Multiobjective Optimization for Railway Maintenance Plans. In: Journal of Computing in Civil Engineering, 32, (3), pp. 04018014, 1-11 (IF 2.554, Q2 in ``Engineering, Civil'' and Q2 in ``Computer Science, Interdisciplinary Applications'', JCR 2018). Abstract bib
  • M. Gonzalez, C. Bergmeir, I. Triguero, Y. Rodriguez, J. M. Benitez (2018) Self-labeling techniques for semi-supervised time series classification: an empirical study. In: Knowledge and Information Systems, 55, (2), pp. 493-528 (IF 2.397, Q2 in ``Computer Science, Information Systems'' and Q2 in ``Computer Science, Artificial Intelligence'', JCR 2018). Abstract DOI bib

2017

  • Christoph Bergmeir, Irma Bilgrami, Christopher Bain, Geoffrey I. Webb, Judit Orosz, David Pilcher (2017) Designing a more efficient, effective and safe Medical Emergency Team (MET) service using data analysis. In: PLoS ONE, 12 (12): e0188688, (12), pp. 1-13 (IF 2.766, Q1 in ``Multidisciplinary Sciences'', JCR 2017). Abstract DOI bib
  • Lahn David Straney, Andrew A Udy, Aidan Burrell, Christoph Bergmeir, Sue Huckson, D James Cooper, David V Pilcher (2017) Modelling risk-adjusted variation in length of stay among Australian and New Zealand ICUs. In: PLoS ONE, 12 (5): e0176570, pp. 1-12 (IF 2.766, Q1 in ``Multidisciplinary Sciences'', JCR 2017). Abstract DOI bib
  • Michelle R. Ananda-Rajah, Christoph Bergmeir, Francois Petitjean, Monica A. Slavin, Karin A. Thursky, Geoffrey I. Webb (2017) Toward Electronic Surveillance of Invasive Mold Diseases in Hematology-Oncology Patients: An Expert System Combining Natural Language Processing of Chest Computed Tomography Reports, Microbiology, and Antifungal Drug Data. In: JCO Clinical Cancer Informatics, (1), pp. 1-10. Abstract DOI bib

2016

  • C. Bergmeir, R. J. Hyndman, J. M. Benitez (2016) Bagging Exponential Smoothing Methods using STL Decomposition and Box-Cox Transformation. In: International Journal of Forecasting, 32, pp. 303-312 (IF 2.642, Q1 in ``Economics'', JCR 2016). Abstract bib
  • C. Bergmeir, D. Molina, J. M. Benitez (2016) Memetic Algorithms with Local Search Chains in R: The Rmalschains Package. In: Journal of Statistical Software, 75, (4), pp. 1-33 (IF 9.436, Q1 in ``Computer Science, Interdisciplinary Research'', and ``Statistics & Probability'', JCR 2016). Abstract DOI  pdf bib
  • M. Gonzalez, C. Bergmeir, I. Triguero, Y. Rodriguez, J. M. Benitez (2016) On the Stopping Criteria for k-Nearest Neighbor in Positive Unlabeled Time Series Classification Problems. In: Information Sciences, 328, pp. 42-59 (IF 4.832, Q1 in ``Computer Science, Information Systems'', JCR 2016). Abstract bib

2015

  • L. S. Riza, C. Bergmeir, F. Herrera, J. M. Benitez (2015) frbs: Fuzzy Rule-Based Systems for Classification and Regression in R. In: Journal of Statistical Software, 65, (6), pp. 1-30 (IF 2.379, Q1 in ``Computer Science, Interdisciplinary Research'', and Q1 in ``Statistics & Probability'', JCR 2015). Abstract DOI  pdf bib

2014

  • L. S. Riza, A. Janusz, C. Bergmeir, C. Cornelis, F. Herrera, D. Slezak, J. M. Benitez (2014) Implementing algorithms of rough set theory and fuzzy rough set theory in the R package ``RoughSets''. In: Information Sciences, 287, (10), pp. 68-89 (IF 4.038, Q1 in ``Computer Science, Information Systems'', JCR 2014). Abstract bib
  • C. Bergmeir, M. Costantini, J. M. Benitez (2014) On the usefulness of cross-validation for directional forecast evaluation. In: Computational Statistics and Data Analysis, 76, pp. 132-143 (IF 1.400, Q2 in ``Statistics & Probability'' and Q3 in ``Computer Science, Interdisciplinary Applications'', JCR 2014). Abstract bib

2013

  • A. Santos-Lozano, F. Santin-Medeiros, G. Cardon, G. Torres-Luque, R. Bailon, C. Bergmeir, J.R. Ruiz, A. Lucia, N. Garatachea (2013) The Actigraph GT3X Accelerometer: validation and determination of physical intensity cut points across age-groups. In: Int J Sports Med., 34, pp. 975-982 (IF 2.374, Q1 in ``Sports Sciences'', JCR 2013). Abstract bib

2012

  • C. Bergmeir, J. M. Benitez (2012) Neural Networks in R Using the Stuttgart Neural Network Simulator: RSNNS. In: Journal of Statistical Software, 46, (7), pp. 1-26 (IF 4.910, Q1 in ``Computer Science, Interdisciplinary Research'', and Q1 in ``Statistics & Probability'', JCR 2012). Abstract DOI  pdf bib
  • C. Bergmeir, J. M. Benitez (2012) On the use of cross-validation for time series predictor evaluation. In: Information Sciences, 191, pp. 192-213 (IF 3.643, Q1 in ``Computer Science, Information Systems'', JCR 2012). Abstract bib
  • C. Bergmeir, M. Garcia Silvente, J. M. Benitez (2012) Segmentation of Cervical Cell Nuclei in High-resolution Microscopic Images: A new Algorithm and a Web-based Software Framework. In: Computer Methods and Programs in Biomedicine, 107, (3), pp. 497-512 (IF 1.555, Q1 in the category ``Computer Science, Theory & Methods'' and Q2 in ``Computer Science, Interdisciplinary Applications'', JCR 2012). Abstract DOI bib
  • C. Bergmeir, I. Triguero, D. Molina, J. L. Aznarte, J. M. Benitez (2012) Time Series Modeling and Forecasting Using Memetic Algorithms for Regime-switching Models. In: IEEE Transactions on Neural Networks and Learning Systems, 23, (11), pp. 1841-1847 (IF 3.766, Q1 ranking in the categories ``Computer Science, Artificial Intelligence'', ``Computer Science, Hardware & Architecture'', and ``Computer Science, Theory & Methods'', JCR 2012). Abstract DOI bib

2009

  • C. Bergmeir, M. Seitel, C. Frank, R. de Simone, H.-P. Meinzer, I. Wolf (2009) Comparing calibration approaches for 3D ultrasound probes. In: International Journal of Computer Assisted Radiology and Surgery, 4, (2), pp. 203-213. Abstract DOI bib

Working papers

2021

  • Md Mohaimenuzzaman, Christoph Bergmeir, Ian Thomas West, Bernd Meyer (2021) Environmental Sound Classification on the Edge: Deep Acoustic Networks for Extremely Resource-Constrained Devices. In: Working Paper. Abstract  pdf bib
  • Hansika Hewamalage, Christoph Bergmeir, Kasun Bandara (2021) Global Models for Time Series Forecasting: A Simulation Study. In: Working Paper. Abstract  pdf bib
  • Chang Wei Tan, Angus Dempster, Christoph Bergmeir, Geoffrey I. Webb (2021) MultiRocket: Effective summary statistics for convolutional outputs in time series classification. In: Working Paper. Abstract  pdf bib
  • Dilini Rajapaksha, Chakkrit Tantithamthavorn, Jirayus Jiarpakdee, Christoph Bergmeir, John Grundy, Wray Buntine (2021) SQAPlanner: Generating Data-Informed Software Quality Improvement Plans. In: Working Paper. Abstract  pdf bib
  • Seyedali Meghdadi, Guido Tack, Ariel Liebman, Nicolas Langrene, Christoph Bergmeir (2021) Versatile and Robust Transient Stability Assessment via Instance Transfer Learning. In: Working Paper. Abstract  pdf bib

2020

  • Rakshitha Godahewa, Christoph Bergmeir, Geoffrey I Webb, Pablo Montero-Manso (2020) A Strong Baseline for Weekly Time Series Forecasting. In: arXiv preprint arXiv:2010.08158. Abstract bib
  • Rakshitha Godahewa, Kasun Bandara, Geoffrey I. Webb, Slawek Smyl, Christoph Bergmeir (2020) Ensembles of Localised Models for Time Series Forecasting. In: Working Paper. Abstract  pdf bib
  • Fotios Petropoulos, Daniele Apiletti, Vassilios Assimakopoulos, Mohamed Zied Babai, Devon K. Barrow, Christoph Bergmeir, Ricardo J. Bessa, John E. Boylan, Jethro Browell, Claudio Carnevale, Jennifer L. Castle, Pasquale Cirillo, Michael P. Clements, Clara Cordeiro, Fernando Luiz Cyrino Oliveira, Shari De Baets, Alexander Dokumentov, Piotr Fiszeder, Philip Hans Franses, Michael Gilliland, M. Sinan Gonul, Paul Goodwin, Luigi Grossi, Yael Grushka-Cockayne, Mariangela Guidolin, Massimo Guidolin, Ulrich Gunter, Xiaojia Guo, Renato Guseo, Nigel Harvey, David F. Hendry, Ross Hollyman, Tim Januschowski, Jooyoung Jeon, Victor Richmond R. Jose, Yanfei Kang, Anne B. Koehler, Stephan Kolassa, Nikolaos Kourentzes, Sonia Leva, Feng Li, Konstantia Litsiou, Spyros Makridakis, Andrew B. Martinez, Sheik Meeran, Theodore Modis, Konstantinos Nikolopoulos, Dilek Onkal, Alessia Paccagnini, Ioannis Panapakidis, Jose M. Pavia, Manuela Pedio, Diego J. Pedregal, Pierre Pinson, Patricia Ramos, David E. Rapach, J. James Reade, Bahman Rostami-Tabar, Michal Rubaszek, Georgios Sermpinis, Han Lin Shang, Evangelos Spiliotis, Aris A. Syntetos, Priyanga Dilini Talagala, Thiyanga S. Talagala, Len Tashman, Dimitrios Thomakos, Thordis Thorarinsdottir, Ezio Todini, Juan Ramon Trapero Arenas, Xiaoqian Wang, Robert L. Winkler, Alisa Yusupova, Florian Ziel (2020) Forecasting: theory and practice. In: Working Paper. Abstract  pdf bib
  • Kasun Bandara, Hansika Hewamalage, Yuan-Hao Liu, Yanfei Kang, Christoph Bergmeir (2020) Improving the Accuracy of Global Forecasting Models using Time Series Data Augmentation. In: arXiv preprint arXiv:2008.02663. Abstract bib
  • Mahdi Abolghasemi, Rob J Hyndman, Garth Tarr, Christoph Bergmeir (2020) Machine learning applications in time series hierarchical forecasting. In: Working Paper. Abstract  pdf bib
  • Mahdi Abolghasemi, Rob Hyndman, Evangelos Spiliotis, Christoph Bergmeir (2020) Model selection in reconciling hierarchical time series. In: arXiv preprint arXiv:2010.10742. Abstract bib
  • Rakshitha Godahewa, Chang Deng, Arnaud Prouzeau, Christoph Bergmeir (2020) Simulation and Optimisation of Air Conditioning Systems using Machine Learning. In: Working Paper. Abstract  pdf bib
  • Chang Wei Tan, Christoph Bergmeir, Francois Petitjean, Geoffrey I. Webb (2020) Time Series Extrinsic Regression. In: Working Paper. Abstract  pdf bib

2016

  • L. S. Riza, C. Bergmeir, F. Herrera, J. M. Benitez (2016) A Universal Representation Framework for Fuzzy Rule-Based Systems Based on PMML. In: Working Paper. Abstract  pdf bib
  • M. Gonzalez, R. Osmani, J.D. Rodriguez, C. Bergmeir, I. Triguero, J. M. Benitez (2016) ssc: An R Package for Semi-Supervised Classification. In: Working Paper. Abstract  pdf bib

Papers in refereed conference proceedings

2020

  • Jahan C Penny-Dimri, Christoph Bergmeir, Christopher M Reid, Jenni Williams-Spence, Andrew D Cochrane, Julian A Smith (2020) Machine Learning Algorithms for Predicting and Risk Profiling of Cardiac Surgery-Associated Acute Kidney Injury. In: Seminars in Thoracic and Cardiovascular Surgery. Abstract bib
  • Rakshitha Godahewa, Trevor Yann, Christoph Bergmeir, Francois Petitjean (2020) Seasonal Averaged One-Dependence Estimators: A Novel Algorithm to Address Seasonal Concept Drift in High-Dimensional Stream Classification. In: International Joint Conference on Neural Networks (IJCNN), 19 - 24 July, 2020, Glasgow (UK). Abstract  pdf bib
  • Satya Borgohain, Gideon Kowadlo, David Rawlinson, Christoph Bergmeir, Kok Loo, Harivallabha Rangarajan, Levin Kuhlmann (2020) Self-organising Neural Network Hierarchy. In: Australasian Joint Conference on Artificial Intelligence, pp. 359-370. Abstract bib
  • Kasun Bandara, Christoph Bergmeir, Sam Campbell, Debbie Scott, Dan Lubman (2020) Towards Accurate Predictions and Causal `What-if' Analyses for Planning and Policy-making: A Case Study in Emergency Medical Services Demand. In: International Joint Conference on Neural Networks (IJCNN), 19 - 24 July, 2020, Glasgow (UK). Abstract  pdf bib

2019

  • H. Bandara, P. Shi, C. Bergmeir, H. Hewamalage, Q. Tran, B. Seaman (2019) Sales Demand Forecast in E-commerce using a Long Short-Term Memory Neural Network Methodology. In: 26th International Conference on Neural Information Processing (ICONIP) 2019, December 12 - 15, Sydney (Australia). Abstract  pdf bib

2014

  • S. Maslyuk, C. Bergmeir, K. Rotaru (2014) Identifying Jumps and Cojumps for Assets of Different Asset Classes. In: Australasian Conference of Economists (ESAM/ACE) 2014, July 1-4, Hobart (Tasmania). Abstract bib
  • L. S. Riza, C. Bergmeir, F. Herrera, J. M. Benitez (2014) Learning from Data Using the R Package ``frbs''. In: Fuzzy Systems (FUZZ-IEEE), 2014 IEEE World Congress on Computational Intelligence (WCCI), July 6-11, Beijing (China). Abstract bib

2013

  • C. Bergmeir, G. Sainz, C. Martinez-Bertrand, J. M. Benitez (2013) A Study on the Use of Machine Learning Methods for Incidence Prediction in High-Speed Train Tracks. In: Proceedings IEA/AIE 2013, June 17-21, Amsterdam (The Netherlands). Abstract bib

2012

  • C. Bergmeir, I. Triguero, F. Velasco, J. M. Benitez (2012) Optimización de Modelos Estadísticos y Difusos para el Análisis de Series Temporales Mediante Evolución Diferencial. In: Actas del XVI Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF2012), Valladolid (Spain), February 2012.. Abstract bib
  • C. Bergmeir, I. Triguero, F. Velasco, J. M. Benitez (2012) Optimization of neuro-coefficient smooth transition autoregressive models using differential evolution. In: Proceedings of the Seventh International Conference on Hybrid Artificial Intelligence Systems (HAIS 2012), Salamanca (Spain). Lecture Notes in Computer Science 7208, pp. 464-473. Abstract bib

2011

  • C. Bergmeir, J. M. Benitez (2011) Forecaster performance evaluation with cross-validation and variants. In: International Conference on Intelligent Systems Design and Applications, ISDA, pp. 849-854. Abstract bib
  • J. M. Benitez, J. L. Aznarte, C. Bergmeir (2011) Research on Time Series at the DiCITS Lab. In: Actas de la XIV Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA11), Tenerife (Spain), November 2011.. Abstract bib

2010

  • C. Bergmeir, M. Garcia Silvente, J. Esquivias Lopez-Cuervo, J. M. Benitez (2010) Segmentation of Cervical Cell Images using Mean-shift Filtering and Morphological Operators. In: Proc. SPIE, Vol. 7623, 76234C. Abstract DOI bib

2009

  • C. Bergmeir, N. Subramanian (2009) Klassifikation von Standardebenen in der 2D-Echokardiographie mittels 2D-3D-Bildregistrierung. In: Bildverarbeitung für die Medizin, Heidelberg: Springer, pp. 222-226. Abstract bib
  • C. Bergmeir, N. Subramanian (2009) Operator Guidance in 2D Echocardiography via 3D Model to Image Registration. In: Proc. SPIE, Vol. 7265, 726518. Abstract DOI bib

2008

  • C. Bergmeir, M. Seitel, C. Frank, R. de Simone, H.-P. Meinzer, I. Wolf (2008) 3D Ultrasound: A Comparison of Calibration Methods. In: International Journal of Computer Assisted Radiology and Surgery. Abstract bib
  • C. Bergmeir, M. Seitel, C. Frank, R. de Simone, H.-P. Meinzer, I. Wolf (2008) Entwicklung und Evaluation einer Kalibrierungsmethode für 3D-Ultraschall. In: Bildverarbeitung für die Medizin, Heidelberg: Springer, pp. 237-241. Abstract bib

Other Conference Publications (Reviewed By Program Committee Alone)

2020

  • Rakshitha Godahewa, Christoph Bergmeir, Geoff Webb (2020) Addressing Data Heterogeneity in Time Series Forecasting using Global Ensemble Models. In: 40th International Symposium on Forecasting (ISF) 2020, October 26 - 28, Virtual (Rio de Janeiro, Brazil). Abstract bib
  • Alexey Chernikov, Christoph Bergmeir, Pablo Montero-Manso (2020) Automatic Feature-based Forecast Model Averaging. In: 40th International Symposium on Forecasting (ISF) 2020, October 26 - 28, Virtual (Rio de Janeiro, Brazil). Abstract bib
  • Hansika Hewamalage, Christoph Bergmeir, Kasun Bandara (2020) Global Models for Time Series Forecasting: A Simulation Study. In: 40th International Symposium on Forecasting (ISF) 2020, October 26 - 28, Virtual (Rio de Janeiro, Brazil). Abstract bib
  • Dilini Rajapaksha, Christoph Bergmeir, Rob J Hyndman (2020) Local Model-Agnostic Interpretability in Global Time Series Forecasting. In: 40th International Symposium on Forecasting (ISF) 2020, October 26 - 28, Virtual (Rio de Janeiro, Brazil). Abstract bib
  • Kasun Bandara, Hansika Hewamalage, Yuan-Hao Liu, Yanfei Kang, Christoph Bergmeir (2020) Transfer Learning Schemes for Global Forecasting Models using Recurrent Neural Networks. In: 40th International Symposium on Forecasting (ISF) 2020, October 26 - 28, Virtual (Rio de Janeiro, Brazil). Abstract bib

2019

  • H. Bandara, C. Bergmeir, H. Hewamalage (2019) Forecasting Time Series with Multiple Seasonal Patterns using a Long Short-Term Memory Neural Network Methodology. In: 39th International Symposium on Forecasting (ISF) 2019, June 16 - 19, Thessaloniki (Greece). Abstract bib
  • S. Smyl, C. Bergmeir (2019) R Rlgt package - Bayesian Extensions of Exponential Smoothing models. In: 39th International Symposium on Forecasting (ISF) 2019, June 16 - 19, Thessaloniki (Greece). Abstract bib
  • H. Hewamalage, C. Bergmeir, H. Bandara (2019) Recurrent Neural Networks for Time Series Forecasting: An Overview and Empirical Evaluations. In: 39th International Symposium on Forecasting (ISF) 2019, June 16 - 19, Thessaloniki (Greece). Abstract bib

2018

  • H. Abdelkarim, M. Durie, K. El-Khawas, R. Bellomo, C. Bergmeir, O. Badawi (2018) Comparison of characteristics and outcomes of patients admitted to the ICU with asthma in Australia, New Zealand and United States. In: Australian Critical Care, Elsevier, pp. 114. Abstract DOI bib
  • M. Gonzalez, R. Osmani, J. Rodriguez, C. Bergmeir, I. Triguero, J. M. Benitez (2018) ssc: An R Package for Semi-Supervised Classification. In: Proceedings useR! 2018, July 10-13, Brisbane (Australia). Abstract bib

2017

  • H. Bandara, C. Bergmeir, S. Smyl (2017) Forecasting Sets of Similar Time Series with Recurrent Neural Networks. In: 37th International Symposium on Forecasting (ISF) 2017, June 26 - 28, Cairns (Australia). Abstract bib

2016

  • C. Bergmeir, R. J. Hyndman, B. Koo (2016) A Note on the Validity of Cross-Validation for Evaluating Time Series Prediction. In: 36th International Symposium on Forecasting (ISF) 2016, June 19 - 22, Santander (Spain). Abstract bib
  • F. Petropoulos, R. J. Hyndman, C. Bergmeir (2016) Exploring the Sources of Uncertainty: Why does Bagging Work?. In: 36th International Symposium on Forecasting (ISF) 2016, June 19 - 22, Santander (Spain). Abstract bib

2015

  • C. Bergmeir, I. Bilgrami, C. Bain, G. Webb, D. Pilcher (2015) Using data mining techniques to build a more efficient medical emergency team service. In: ANZICS, Safety and Quality Conference: The Deteriorating Patient, July 6-7, Gold Coast, Australia. Abstract bib

2014

  • C. Bergmeir, R. J. Hyndman, J. M. Benitez (2014) Bagging Exponential Smoothing Methods using STL Decomposition and Box-Cox Transformation. In: 34th International Symposium on Forecasting (ISF) 2014, June 29 - July 2, Rotterdam (The Netherlands). Abstract bib
  • J. M. Benitez, L. S. Riza, C. Bergmeir, D. Peralta, F. Herrera (2014) R as a PaaS cloud computing service for Computational Intelligence tasks. In: Proceedings useR! 2014, June 30 - July 3, Los Angeles (California). Abstract bib

2013

  • L. S. Riza, C. Bergmeir, F. Herrera, J. M. Benitez (2013) Constructing fuzzy rule-based systems with the R package frbs. In: Proceedings useR! 2013, July 10-12, Albacete (Spain). Abstract bib
  • C. Bergmeir, M. Costantini, J. M. Benitez (2013) On the usefulness of the cross-validation for directional forecast evaluation. In: 7th International Conference on Computational and Financial Econometrics 2013, December 2013, London. Abstract bib
  • C. Bergmeir, J. M. Benitez, J. Bermudez, J.V. Segura, E. Vercher (2013) Rsiopred: An R package for forecasting by exponential smoothing with model selection by a fuzzy multicriteria approach. In: Proceedings useR! 2013, July 10-12, Albacete (Spain). Abstract bib