Fabio Aiolli

Artificial Intelligence · 2009–2021

A researcher in the Science corpus: 3 papers; trusts 23 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 56 citations into it; #13,744 of 35,345 by trust here, #25,040 by citations
• Natural Language Processing — 48 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it; #21,080 of 21,575 by trust here, #20,271 by citations
• Information Systems — 12 citations into it; #2,714 of 8,771 by trust here, #7,705 by citations

Whom Fabio Aiolli trusts overall

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

1. George Karypis
2. Mukund Deshpande
3. Feng Niu
4. Xiaoyuan Su
5. Gary G. Yen
6. Shumeet Baluja
7. Michael Collins
8. Taghi M. Khoshgoftaar
9. Paolo Frasconi
10. Yehuda Koren

Who trusts Fabio Aiolli overall

1. Harald Steck
2. Markus Schedl
3. Davide Bacciu
4. Hamed Zamani
5. Ching-Wei Chen
6. Charu C. Aggarwal
7. Alessio Micheli
8. Alessandro Sperduti
9. Yashar Deldjoo

Papers from Fabio Aiolli's perspective

Ordered by how strongly the researchers Fabio Aiolli 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Efficient top-n recommendation for very large scale binary rated datasets (2013) — 129 citations
• An introduction to Deep Learning in Natural Language Processing: Models, techniques, and tools (2021) — 579 citations
• Learning Nonsparse Kernels by Self-Organizing Maps for Structured Data (2009) — 27 citations