Alexander Tuzhilin

Information Systems · 2005–2019

A researcher in the Science corpus: 7 papers; trusts 98 researchers and is trusted by 185 researchers here, as inferred from the citation graph.

Subfields

• Information Systems — 65 citations into it; #53 of 8,771 by trust here, #100 by citations
• Artificial Intelligence — 52 citations into it
• Computer Vision and Pattern Recognition — 32 citations into it; #2,554 of 21,575 by trust here, #1,869 by citations
• Recommender Systems — 20 citations into it; #8 of 233 by trust here, #15 by citations
• Management Science and Operations Research — 17 citations into it; #154 of 11,946 by trust here, #210 by citations
• Computer Networks and Communications — 16 citations into it
• Signal Processing — 13 citations into it; #1,057 of 7,572 by trust here, #1,170 by citations
• Marketing — 9 citations into it

Whom Alexander Tuzhilin trusts overall

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

1. Michael J. Pazzani
2. Thomas Hofmann
3. Yehuda Koren
4. Daniel Billsus
5. J. Konstan
6. Paul Resnick
7. Badrul Munir Sarwar
8. Diederik P. Kingma
9. Ken Lang
10. Robin D. Burke

Who trusts Alexander Tuzhilin overall

1. Panniello Umberto
2. Jesús Bobadilla
3. Francesco Ricci
4. Charu C. Aggarwal
5. Gediminas Adomavicius
6. Jie Lu
7. Li Chen
8. Sotirios P. Chatzis
9. Dietmar Jannach
10. Balázs Hidasi

Papers from Alexander Tuzhilin's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions (2005) — 10,751 citations
• Context-aware recommender systems (2008) — 2,304 citations
• Incorporating contextual information in recommender systems using a multidimensional approach (2005) — 1,308 citations
• Aspect Based Recommendations: Recommending Items with the Most Valuable Aspects Based on User Reviews (2017) — 199 citations
• DDTCDR: Deep Dual Transfer Cross Domain Recommendation (2019) — 327 citations
• An energy-efficient mobile recommender system (2010) — 371 citations
• The long tail of recommender systems and how to leverage it (2008) — 490 citations