Thomas F. Boucher
Artificial Intelligence · 2015
A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 6 citations into it
- Statistical Learning Theory — 5 citations into it
- Statistics and Probability — 5 citations into it
Whom Thomas F. Boucher trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Chih-Jen Lin
- Christopher K. I. Williams
- Leo Breiman
- Eric R. Ziegel
- Max Kuhn
- Bernhard Schölkopf
- Rong-En Fan
- Alex Smola
- Ian T. Jolliffe
- Fabian Pedregosa
Papers from Thomas F. Boucher's perspective
Ordered by how strongly the researchers Thomas F. Boucher 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)
- LIBSVM: A library for support vector machines
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- The Elements of Statistical Learning
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)