Dirk Van den Poel
Economics and Econometrics · 2005–2015
A researcher in the Science corpus: 8 papers; trusts 41 researchers and is trusted by 26 researchers here, as inferred from the citation graph.
Subfields
- Economics and Econometrics — 63 citations into it
- Artificial Intelligence — 39 citations into it; #15,512 of 35,345 by trust here, #16,771 by citations
- Statistics and Probability — 34 citations into it
- Marketing — 27 citations into it; #591 of 6,289 by trust here, #937 by citations
- Management Science and Operations Research — 19 citations into it; #8,031 of 11,946 by trust here, #6,314 by citations
- Organizational Behavior and Human Resource Management — 12 citations into it; #1,684 of 8,741 by trust here, #3,852 by citations
- Optimization & Training — 11 citations into it
- Evaluation & Benchmarks — 10 citations into it
Whom Dirk Van den Poel trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jerome H. Friedman
- Thomas G. Dietterich
- Gary M. Weiss
- David John Cameron MacKay
- Yuhai Wu
- Yoav Freund
- F. Economie
- W. Buckinx
- Leo Breiman
- Trevor J. Hastie
Who trusts Dirk Van den Poel overall
- Jonathan Burez
- Wouter Verbeke
- Marcel Karnstedt
- Farshad Kooti
- Eric Wai Ting Ngai
- Weiwei Jiang
- Abdelrahim Kasem Ahmad
- M. D. Canniére
- Ehsan Hoseinzade
- Karel Dejaeger
Papers from Dirk Van den Poel's perspective
Ordered by how strongly the researchers Dirk Van den Poel trusts endorse each paper. Same corpus, a different order for every researcher.
- The Nature of Statistical Learning Theory
- Statistical Learning Theory
- An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization
- A decision-theoretic generalization of on-line learning and an application to boosting
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Bagging Predictors
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
Their papers
- Binary quantile regression: a Bayesian approach based on the asymmetric Laplace distribution (2012) — 119 citations
- Evaluating multiple classifiers for stock price direction prediction (2015) — 554 citations
- Empathy as added value in predicting donation behavior (2011) — 206 citations
- The Kinked Demand Curve and Price Rigidity: Evidence from Scanner Data (2010) — 138 citations
- Handling class imbalance in customer churn prediction (2009) — 570 citations
- Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques (2008) — 471 citations
- Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting (2005) — 462 citations
- Predicting online-purchasing behaviour (2005) — 304 citations