Mike Wells

Artificial Intelligence · 2007

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it
• Natural Language Processing — 9 citations into it

Whom Mike Wells trusts overall

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

1. Michael Collins
2. Charles Sutton
3. Lawrence R. Rabiner
4. Andrew McCallum
5. Koby Crammer

Papers from Mike Wells's perspective

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

1. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. A tutorial on hidden Markov models and selected applications in speech recognition
8. Max-Margin Markov Networks
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Gradient-based learning applied to document recognition

Their papers

• Structured Models for Fine-to-Coarse Sentiment Analysis (2007) — 336 citations