Sven F. Crone

Management Science and Operations Research · 2008–2016

A researcher in the Science corpus: 6 papers; trusts 72 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Management Science and Operations Research — 86 citations into it; #1,733 of 11,946 by trust here, #2,108 by citations
• Economics and Econometrics — 50 citations into it
• Artificial Intelligence — 44 citations into it; #9,242 of 35,345 by trust here, #19,439 by citations
• Statistics and Probability — 27 citations into it
• Evaluation & Benchmarks — 20 citations into it
• Time-Series & Forecasting — 18 citations into it
• Optimization & Training — 13 citations into it
• Electrical and Electronic Engineering — 12 citations into it; #10,331 of 16,539 by trust here, #11,977 by citations

Whom Sven F. Crone trusts overall

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

1. Spyros Makridakis
2. M. Hibon
3. Leo Breiman
4. Yoav Freund
5. Robert E. Schapire
6. Rob J Hyndman
7. Jerome H. Friedman
8. Andreas S. Weigend
9. Robert Fildes
10. Niko Speybroeck

Who trusts Sven F. Crone overall

1. Kasun Bandara
2. Christoph Bergmeir
3. Fotios Petropoulos
4. Devon K. Barrow
5. Weizhong Yan
6. Hansika Hewamalage
7. Md. Mustafizur Rahman
8. Mirko Kück
9. Slawek Smyl
10. Spyros Makridakis

Papers from Sven F. Crone's perspective

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

1. Bagging Predictors
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Regression Shrinkage and Selection via the Lasso
4. ImageNet classification with deep convolutional neural networks
5. The Nature of Statistical Learning Theory
6. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. Estimating the Dimension of a Model
9. Gradient-based learning applied to document recognition
10. The Elements of Statistical Learning

Their papers

• A comparison of AdaBoost algorithms for time series forecast combination (2016) — 68 citations
• Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction (2011) — 278 citations
• Meta-learning with neural networks and landmarking for forecasting model selection an empirical evaluation of different feature sets applied to industry data (2016) — 41 citations
• Neural network ensemble operators for time series forecasting (2014) — 314 citations
• Forecasting and operational research: a review (2008) — 296 citations
• An evaluation of neural network ensembles and model selection for time series prediction (2010) — 43 citations