B. Michael Kelm
Artificial Intelligence · 2009–2015
A researcher in the Science corpus: 3 papers; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 15 citations into it
- Statistics and Probability — 14 citations into it
- Computer Vision and Pattern Recognition — 9 citations into it
- Statistical Learning Theory — 9 citations into it
- Analytical Chemistry — 7 citations into it
- Evaluation & Benchmarks — 7 citations into it
- Computational Theory and Mathematics — 5 citations into it
Whom B. Michael Kelm trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Leo Breiman
- Trevor J. Hastie
- Zhuowen Tu
- Andy Liaw
- Thomas G. Dietterich
- Eric R. Ziegel
- Tin Kam Ho
- J. Platt
- Mark R. Segal
- Yoav Freund
Who trusts B. Michael Kelm overall
Papers from B. Michael Kelm's perspective
Ordered by how strongly the researchers B. Michael Kelm trusts endorse each paper. Same corpus, a different order for every researcher.
- Bagging Predictors
- Random Forests
- ImageNet classification with deep convolutional neural networks
- A decision-theoretic generalization of on-line learning and an application to boosting
- The Elements of Statistical Learning
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet: A large-scale hierarchical image database
- The Nature of Statistical Learning Theory
Their papers
- On Oblique Random Forests (2011) — 256 citations
- A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data (2009) — 1,177 citations
- Left Atrial Segmentation Challenge 2013: MRI training (2015)