Thomas Finley
Artificial Intelligence · 2007–2017
A researcher in the Science corpus: 4 papers; trusts 50 researchers and is trusted by 212 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 36 citations into it; #1,306 of 35,345 by trust here, #3,673 by citations
- Optimization & Training — 17 citations into it; #211 of 2,601 by trust here, #309 by citations
- Computer Vision and Pattern Recognition — 12 citations into it; #6,515 of 21,575 by trust here, #7,340 by citations
- Natural Language Processing — 11 citations into it
- Information Systems — 8 citations into it; #1,494 of 8,771 by trust here, #1,489 by citations
- Evaluation & Benchmarks — 7 citations into it
- Statistical Learning Theory — 5 citations into it
- Signal Processing — 5 citations into it
Whom Thomas Finley trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Thorsten Joachims
- Ioannis Tsochantaridis
- Vladimir Kolmogorov
- Michael Collins
- Kevin P. Murphy
- John D. Lafferty
- Vladimir Naumovich Vapnik
- B. Taskar
- Yuri Boykov
- Koby Crammer
Who trusts Thomas Finley overall
- Hema Swetha Koppula
- Abhishek Anand
- Ashutosh Saxena
- Thorsten Joachims
- Yi Yang
- Deva Ramanan
- Yisong Yue
- Simon Lacoste-Julien
- Andrea Vedaldi
- Andrew Zisserman
Papers from Thomas Finley's perspective
Ordered by how strongly the researchers Thomas Finley trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- A support vector method for optimizing average precision (2007) — 777 citations
- Cutting-plane training of structural SVMs (2009) — 1,126 citations
- Training structural SVMs when exact inference is intractable (2008) — 312 citations
- LightGBM: A Highly Efficient Gradient Boosting Decision Tree (2017) — 15,550 citations