T. R. Hoens

Artificial Intelligence · 2011–2016

A researcher in the Science corpus: 3 papers; trusts 12 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it; #20,389 of 35,345 by trust here, #22,463 by citations
• Computer Vision and Pattern Recognition — 12 citations into it; #16,316 of 21,575 by trust here, #12,689 by citations
• Information Systems — 7 citations into it; #4,265 of 8,771 by trust here, #4,885 by citations
• Statistical Learning Theory — 6 citations into it
• Evaluation & Benchmarks — 5 citations into it
• Optimization & Training — 5 citations into it

Whom T. R. Hoens trusts overall

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

1. Leo Breiman
2. Thomas G. Dietterich
3. Nitesh V. Chawla
4. J. Ross Quinlan
5. Geoffrey E. Hinton
6. Chih-Jen Lin
7. Niko Speybroeck
8. Jaka Demsar
9. Yoav Freund
10. Peter A. Flach

Who trusts T. R. Hoens overall

1. Octavio Loyola-González
2. Xiangnan He
3. Xiang Wang
4. Siong Thye Goh
5. Andrea Dal Pozzolo
6. Paula Branco
7. Aida Ali
8. Felix Last
9. Damien Dablain
10. Wenhao Lu

Papers from T. R. Hoens's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features (2016) — 456 citations
• Hellinger distance decision trees are robust and skew-insensitive (2011)
• Hellinger distance decision trees are robust and skew-insensitive (2011) — 251 citations