Longbing Cao

Artificial Intelligence · ACM Computing Surveys · 2006–2021

A researcher in the Science corpus: 16 papers; trusts 409 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 220 citations into it; #34,491 of 35,345 by trust here, #10,430 by citations
• Information Systems — 133 citations into it; #3,867 of 8,771 by trust here, #1,443 by citations
• Computer Vision and Pattern Recognition — 86 citations into it; #21,003 of 21,575 by trust here, #19,310 by citations
• Management Science and Operations Research — 71 citations into it; #8,633 of 11,946 by trust here, #4,430 by citations
• Signal Processing — 42 citations into it; #5,032 of 7,572 by trust here, #7,324 by citations
• Computer Networks and Communications — 39 citations into it; #6,478 of 9,886 by trust here, #6,788 by citations
• Computational Theory and Mathematics — 25 citations into it
• Recommender Systems — 24 citations into it

Whom Longbing Cao trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Roy Rada
4. Roger B. Myerson
5. Jem N. Corcoran
6. Cesare Fracassi
7. Alex Krizhevsky
8. Yann LeCun
9. Ilya Sutskever
10. Diederik P. Kingma

Who trusts Longbing Cao overall

1. Amir-Hossein Karimi
2. Gilles Barthe
3. José Ramón Saura
4. Bernhard Schölkopf
5. Gabriele Tolomei
6. Isabel Valera
7. Xi Zhang
8. Patrick Mikalef
9. John Howard
10. M. M. Afsar

Papers from Longbing Cao's perspective

Ordered by how strongly the researchers Longbing Cao 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. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Flexible Frameworks for Actionable Knowledge Discovery (2010) — 100 citations
• Training deep neural networks on imbalanced data sets (2016) — 452 citations
• Sequential Recommender Systems: Challenges, Progress and Prospects (2019) — 517 citations
• A Survey on Session-based Recommender Systems (2019) — 614 citations
• What Is Data Science (2018) — 568 citations
• USpan: an efficient algorithm for mining high utility sequential patterns (2012) — 301 citations
• AI in Finance: Challenges, Techniques, and Opportunities (2021) — 436 citations
• Deep Learning for Anomaly Detection (2020) — 1,385 citations
• Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2015) — 63 citations
• Coupled Matrix Factorization Within Non-IID Context (2014) — 20 citations
• Personalized recommendation via cross-domain triadic factorization (2013) — 273 citations
• Effective detection of sophisticated online banking fraud on extremely imbalanced data (2012) — 343 citations
• Coupled nominal similarity in unsupervised learning (2011) — 90 citations
• SMILE: A Similarity-Based Approach for Multiple Instance Learning (2010) — 14 citations
• Knowledge actionability: satisfying technical and business interestingness (2007) — 62 citations
• Domain-Driven Actionable Knowledge Discovery in the Real World (2006) — 55 citations