Ainur Yessenalina

Artificial Intelligence · 2008–2012

A researcher in the Science corpus: 4 papers; trusts 49 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 47 citations into it; #16,411 of 35,345 by trust here, #17,776 by citations
• Natural Language Processing — 34 citations into it; #1,695 of 5,688 by trust here, #3,053 by citations
• Optimization & Training — 9 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it; #10,415 of 21,575 by trust here, #11,950 by citations
• Evaluation & Benchmarks — 5 citations into it; #1,508 of 3,147 by trust here, #2,166 by citations
• Representation & Self-Supervised Learning — 5 citations into it

Whom Ainur Yessenalina trusts overall

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

1. Janyce Wiebe
2. Bo Pang
3. Theresa Wilson
4. Omar Zaidan
5. Koby Crammer
6. Thorsten Joachims
7. S. Rudolph
8. Lillian Lee
9. Pedro F. Felzenszwalb
10. Alan L. Yuille

Who trusts Ainur Yessenalina overall

1. Lei Zhang
2. Richard Socher
3. Quoc V. Le
4. Dani Yogatama
5. Minlie Huang
6. Duyu Tang
7. Qiao Qian
8. B. Liu
9. Noah A. Smith
10. Eunsol Choi

Papers from Ainur Yessenalina's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• An empirical evaluation of supervised learning in high dimensions (2008) — 593 citations
• Computational Approaches to Sentence Completion (2012) — 55 citations
• Compositional Matrix-Space Models for Sentiment Analysis (2011) — 165 citations
• Multi-Level Structured Models for Document-Level Sentiment Classification (2010) — 212 citations