Vassilios Assimakopoulos

Management Science and Operations Research · 1995–2020

A researcher in the Science corpus: 18 papers; trusts 42 researchers and is trusted by 44 researchers here, as inferred from the citation graph.

Subfields

• Management Science and Operations Research — 327 citations into it; #490 of 11,946 by trust here, #457 by citations
• Economics and Econometrics — 281 citations into it; #1,719 of 23,481 by trust here, #3,392 by citations
• Statistics and Probability — 154 citations into it; #4,010 of 12,932 by trust here, #3,038 by citations
• Finance — 116 citations into it
• Artificial Intelligence — 108 citations into it
• Signal Processing — 74 citations into it; #5,364 of 7,572 by trust here, #3,428 by citations
• Time-Series & Forecasting — 73 citations into it; #15 of 381 by trust here, #24 by citations
• Electrical and Electronic Engineering — 68 citations into it

Whom Vassilios Assimakopoulos trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Spyros Makridakis
2. Rob J Hyndman
3. Everette S. Gardner Jr.
4. Fotios Petropoulos
5. M. Hibon
6. Paul Goodwin
7. Konstantinos Nikolopoulos
8. Stephan Kolassa
9. A. Syntetos
10. Dimitrios D. Thomakos

Who trusts Vassilios Assimakopoulos overall

1. Fotios Petropoulos
2. Konstantinos Nikolopoulos
3. Evangelos Spiliotis
4. Rob J Hyndman
5. Spyros Makridakis
6. Rafal Weron
7. Boris N. Oreshkin
8. Maciej Pawlikowski
9. Raul Poler Escoto
10. Yanfei Kang

Papers from Vassilios Assimakopoulos's perspective

Ordered by how strongly the researchers Vassilios Assimakopoulos trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Estimating the Dimension of a Model
3. Bagging Predictors
4. Regression Shrinkage and Selection via the Lasso
5. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation
6. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
7. Generalized autoregressive conditional heteroskedasticity
8. Improving neural networks by preventing co-adaptation of feature detectors
9. The Elements of Statistical Learning
10. Combining forecasts: A review and annotated bibliography

Their papers

• The theta model: a decomposition approach to forecasting (2000) — 505 citations
• The M4 Competition: 100,000 time series and 61 forecasting methods (2020) — 970 citations
• Forecasting with a hybrid method utilizing data smoothing, a variation of the Theta method and shrinkage of seasonal factors (2018) — 28 citations
• The Theta Model: An Essential Forecasting Tool for Supply Chain Planning (2011) — 21 citations
• The M4 Competition: Results, findings, conclusion and way forward (2018) — 686 citations
• 'Horses for Courses' in demand forecasting (2014) — 210 citations
• A systemic view of the ADIDA framework (2014) — 30 citations
• Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018) — 1,376 citations
• Real estate appraisal: a review of valuation methods (2003) — 448 citations
• Are forecasting competitions data representative of the reality? (2020) — 79 citations
• Forecasting: theory and practice (2020) — 551 citations
• Predicting/hypothesizing the findings of the M4 Competition (2020) — 31 citations
• Tales from tails: On the empirical distributions of forecasting errors and their implication to risk (2019) — 11 citations
• Objectivity, reproducibility and replicability in forecasting research (2018)
• A neural network approach for the Theta model (2012) — 6 citations
• Theta intelligent forecasting information system (2003) — 41 citations
• Etifis: An Innovative e-Forecasting Web Application (2003) — 8 citations
• A successive filtering technique for identifying long-term trends (1995)