W. Philip Kegelmeyer Jr.

Artificial Intelligence · 2002–2012

A researcher in the Science corpus: 4 papers; trusts 17 researchers and is trusted by 124 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it; #2,106 of 35,345 by trust here, #1,878 by citations
• Evaluation & Benchmarks — 9 citations into it
• Information Systems — 7 citations into it; #4,266 of 8,771 by trust here, #4,885 by citations
• Statistical Learning Theory — 7 citations into it; #139 of 1,038 by trust here, #48 by citations
• Natural Language Processing — 7 citations into it

Whom W. Philip Kegelmeyer Jr. trusts overall

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

1. Leo Breiman
2. J. Ross Quinlan
3. T. Griffiths
4. Thomas G. Dietterich
5. David M. Blei
6. Nitesh V. Chawla
7. Daniel D. Lee
8. William W. Cohen
9. Chih-Jen Lin
10. Jaka Demsar

Who trusts W. Philip Kegelmeyer Jr. overall

1. Nitesh V. Chawla
2. Alberto Fernández
3. Andrea Dal Pozzolo
4. Shuo Wang
5. Octavio Loyola-González
6. Taghi M. Khoshgoftaar
7. Bartosz Krawczyk
8. Francisco Herrera
9. David A. Cieslak
10. Victoria López

Papers from W. Philip Kegelmeyer Jr.'s perspective

Ordered by how strongly the researchers W. Philip Kegelmeyer Jr. trusts endorse each paper. Same corpus, a different order for every researcher.

1. Gradient-based learning applied to document recognition
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. Latent Dirichlet Allocation
6. LIBSVM: A library for support vector machines
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Attention is All you Need (Neural Information Processing Systems)
10. Random Forests

Their papers

• SMOTE: Synthetic Minority Over-sampling Technique (2002) — 31,281 citations
• Exploring Topic Coherence over Many Models and Many Topics (2012) — 573 citations
• Hellinger distance decision trees are robust and skew-insensitive (2011)
• Hellinger distance decision trees are robust and skew-insensitive (2011) — 251 citations