Rob J. Hyndman

Publication Activity (10 Years)

Years Active: 2004-2023
Publications (10 Years): 35

Top Topics

High Dimensional

Outlier Detection

Machine Learning

Top Venues

J. Comput. Graph. Stat.

Eur. J. Oper. Res.

Publications

Anastasios Panagiotelis, Puwasala Gamakumara, George Athanasopoulos, Rob J. Hyndman
Probabilistic forecast reconciliation: Properties, evaluation and score optimisation. Eur. J. Oper. Res. 306 (2) (2023)
Sayani Gupta, Rob J. Hyndman, Dianne Cook, Antony Unwin
Visualizing Probability Distributions Across Bivariate Cyclic Temporal Granularities. J. Comput. Graph. Stat. 31 (1) (2022)
Sevvandi Kandanaarachchi, Rob J. Hyndman
Anomaly detection in dynamic networks. CoRR (2022)
Sevvandi Kandanaarachchi, Rob J. Hyndman
Leave-One-Out Kernel Density Estimates for Outlier Detection. J. Comput. Graph. Stat. 31 (1) (2022)
Mahdi Abolghasemi, Rob J. Hyndman, Evangelos Spiliotis, Christoph Bergmeir
Model selection in reconciling hierarchical time series. Mach. Learn. 111 (2) (2022)
Mahsa Ashouri, Rob J. Hyndman, Galit Shmueli
Fast Forecast Reconciliation Using Linear Models. J. Comput. Graph. Stat. 31 (1) (2022)
Rakshitha Godahewa, Christoph Bergmeir, Geoffrey I. Webb, Rob J. Hyndman, Pablo Montero-Manso
Monash Time Series Forecasting Archive. CoRR (2021)
Evangelos Spiliotis, Mahdi Abolghasemi, Rob J. Hyndman, Fotios Petropoulos, Vassilios Assimakopoulos
Hierarchical forecast reconciliation with machine learning. Appl. Soft Comput. 112 (2021)
Insha Ullah, Kerrie L. Mengersen, Rob J. Hyndman, James McGree
Detection of cybersecurity attacks through analysis of web browsing activities using principal component analysis. CoRR (2021)
Priyanga Dilini Talagala, Rob J. Hyndman, Kate Smith-Miles
Anomaly Detection in High-Dimensional Data. J. Comput. Graph. Stat. 30 (2) (2021)
Rakshitha Godahewa, Christoph Bergmeir, Geoffrey I. Webb, Rob J. Hyndman, Pablo Montero-Manso
Monash Time Series Forecasting Archive. NeurIPS Datasets and Benchmarks (2021)
Hansika Hewamalage, Pablo Montero-Manso, Christoph Bergmeir, Rob J. Hyndman
A Look at the Evaluation Setup of the M5 Forecasting Competition. CoRR (2021)
Dilini Rajapaksha, Christoph Bergmeir, Rob J. Hyndman
LoMEF: A Framework to Produce Local Explanations for Global Model Time Series Forecasts. CoRR (2021)
Sevvandi Kandanaarachchi, Rob J. Hyndman
Dimension Reduction for Outlier Detection Using DOBIN. J. Comput. Graph. Stat. 30 (1) (2021)
Florian Eckert, Rob J. Hyndman, Anastasios Panagiotelis
Forecasting Swiss exports using Bayesian forecast reconciliation. Eur. J. Oper. Res. 291 (2) (2021)
Fan Cheng, Rob J. Hyndman, Anastasios Panagiotelis
Manifold learning with approximate nearest neighbors. CoRR (2021)
Bahman Rostami Tabar, Mohammad M. Ali, Tao Hong, Rob J. Hyndman, Michael D. Porter, Aris A. Syntetos
Forecasting for Social Good. CoRR (2020)
Evangelos Spiliotis, Mahdi Abolghasemi, Rob J. Hyndman, Fotios Petropoulos, Vassilios Assimakopoulos
Hierarchical forecast reconciliation with machine learning. CoRR (2020)
Shanika L. Wickramasuriya, Berwin A. Turlach, Rob J. Hyndman
Optimal non-negative forecast reconciliation. Stat. Comput. 30 (5) (2020)
Yanfei Kang, Rob J. Hyndman, Feng Li
GRATIS: GeneRAting TIme Series with diverse and controllable characteristics. Stat. Anal. Data Min. 13 (4) (2020)
Sevvandi Kandanaarachchi, Mario A. Muñoz, Rob J. Hyndman, Kate Smith-Miles
On normalization and algorithm selection for unsupervised outlier detection. Data Min. Knowl. Discov. 34 (2) (2020)
Mahdi Abolghasemi, Rob J. Hyndman, Evangelos Spiliotis, Christoph Bergmeir
Model selection in reconciling hierarchical time series. CoRR (2020)
Pablo Montero-Manso, Rob J. Hyndman
Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality. CoRR (2020)
Mahdi Abolghasemi, Rob J. Hyndman, Garth Tarr, Christoph Bergmeir
Machine learning applications in time series hierarchical forecasting. CoRR (2019)
Yanfei Kang, Rob J. Hyndman, Feng Li
GRATIS: GeneRAting TIme Series with diverse and controllable characteristics. CoRR (2019)
Priyanga Dilini Talagala, Rob J. Hyndman, Kate Smith-Miles
Anomaly Detection in High Dimensional Data. CoRR (2019)
Christoph Bergmeir, Rob J. Hyndman, Bonsoo Koo
A note on the validity of cross-validation for evaluating autoregressive time series prediction. Comput. Stat. Data Anal. 120 (2018)
Fotios Petropoulos, Rob J. Hyndman, Christoph Bergmeir
Exploring the sources of uncertainty: Why does bagging for time series forecasting work? Eur. J. Oper. Res. 268 (2) (2018)
Anne Driemel, Rob J. Hyndman, Galit Shmueli
Analysing Large Collections of Time Series (NII Shonan Meeting 2018-3). NII Shonan Meet. Rep. 2018 (2018)
Souhaib Ben Taieb, James W. Taylor, Rob J. Hyndman
Coherent Probabilistic Forecasts for Hierarchical Time Series. ICML (2017)
Paul Goodwin, Fotios Petropoulos, Rob J. Hyndman
A note on upper bounds for forecast-value-added relative to naïve forecasts. J. Oper. Res. Soc. 68 (9) (2017)
Ingrida Steponavice, Rob J. Hyndman, Kate Smith-Miles, Laura Villanova
Dynamic algorithm selection for pareto optimal set approximation. J. Glob. Optim. 67 (1-2) (2017)
George Athanasopoulos, Rob J. Hyndman, Nikolaos Kourentzes, Fotios Petropoulos
Forecasting with temporal hierarchies. Eur. J. Oper. Res. 262 (1) (2017)
Rob J. Hyndman, Alan J. Lee, Earo Wang
Fast computation of reconciled forecasts for hierarchical and grouped time series. Comput. Stat. Data Anal. 97 (2016)
Souhaib Ben Taieb, Raphaël Huser, Rob J. Hyndman, Marc G. Genton
Forecasting Uncertainty in Electricity Smart Meter Data by Boosting Additive Quantile Regression. IEEE Trans. Smart Grid 7 (5) (2016)
Rob J. Hyndman, Earo Wang, Nikolay Laptev
Large-Scale Unusual Time Series Detection. ICDM Workshops (2015)
Ingrida Steponavice, Rob J. Hyndman, Kate Smith-Miles, Laura Villanova
Efficient Identification of the Pareto Optimal Set. LION (2014)
Souhaib Ben Taieb, Rob J. Hyndman
Boosting multi-step autoregressive forecasts. ICML (2014)
Han Lin Shang, Rob J. Hyndman
Nonparametric time series forecasting with dynamic updating. Math. Comput. Simul. 81 (7) (2011)
Rob J. Hyndman, Roman A. Ahmed, George Athanasopoulos, Han Lin Shang
Optimal combination forecasts for hierarchical time series. Comput. Stat. Data Anal. 55 (9) (2011)
Jae H. Kim, Iain Fraser, Rob J. Hyndman
Improved interval estimation of long run response from a dynamic linear model: A highest density region approach. Comput. Stat. Data Anal. 55 (8) (2011)
Laura Villanova, Paolo Falcaro, Davide Carta, Irene Poli, Rob J. Hyndman, Kate Smith-Miles
Functionalization of microarray devices: Process optimization using a multiobjective PSO and multiresponse MARS modeling. IEEE Congress on Evolutionary Computation (2010)
Xiaozhe Wang, Kate Amanda Smith-Miles, Rob J. Hyndman
Rule induction for forecasting method selection: Meta-learning the characteristics of univariate time series. Neurocomputing 72 (10-12) (2009)
Phillip G. Gould, Anne B. Koehler, J. Keith Ord, Ralph D. Snyder, Rob J. Hyndman, Farshid Vahid-Araghi
Forecasting time series with multiple seasonal patterns. Eur. J. Oper. Res. 191 (1) (2008)
Jae H. Kim, Param Silvapulle, Rob J. Hyndman
Half-life estimation based on the bias-corrected bootstrap: A highest density region approach. Comput. Stat. Data Anal. 51 (7) (2007)
Rob J. Hyndman, Md. Shahid Ullah
Robust forecasting of mortality and fertility rates: A functional data approach. Comput. Stat. Data Anal. 51 (10) (2007)
Xibin Zhang, Maxwell L. King, Rob J. Hyndman
A Bayesian approach to bandwidth selection for multivariate kernel density estimation. Comput. Stat. Data Anal. 50 (11) (2006)
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman
Characteristic-Based Clustering for Time Series Data. Data Min. Knowl. Discov. 13 (3) (2006)
A. V. Kostenko, Rob J. Hyndman
A note on the categorization of demand patterns. J. Oper. Res. Soc. 57 (10) (2006)
Denny Meyer, Rob J. Hyndman
The accuracy of television network rating forecasts: The effects of data aggregation and alternative models. Model. Assist. Stat. Appl. 1 (3) (2006)
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman
Dimension Reduction for Clustering Time Series Using Global Characteristics. International Conference on Computational Science (3) (2005)
Ralph D. Snyder, Anne B. Koehler, Rob J. Hyndman, J. Keith Ord
Exponential smoothing models: Means and variances for lead-time demand. Eur. J. Oper. Res. 158 (2) (2004)