Quanming Yao

9.6k total citations · 3 hit papers
88 papers, 4.3k citations indexed

About

Quanming Yao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Quanming Yao has authored 88 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Artificial Intelligence, 42 papers in Computer Vision and Pattern Recognition and 15 papers in Information Systems. Recurrent topics in Quanming Yao's work include Advanced Graph Neural Networks (28 papers), Topic Modeling (16 papers) and Sparse and Compressive Sensing Techniques (14 papers). Quanming Yao is often cited by papers focused on Advanced Graph Neural Networks (28 papers), Topic Modeling (16 papers) and Sparse and Compressive Sensing Techniques (14 papers). Quanming Yao collaborates with scholars based in China, Hong Kong and Japan. Quanming Yao's co-authors include James T. Kwok, Yaqing Wang, Lionel M. Ni, Huan Zhao, Bo Han, Gang Niu, Masashi Sugiyama, Ivor W. Tsang, Dik Lun Lee and Miao Xu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Quanming Yao

83 papers receiving 4.2k citations

Hit Papers

Generalizing from a Few Examples 2017 2026 2020 2023 2020 2018 2017 500 1000 1.5k

Peers

Quanming Yao
Comparison fields: 5 of 160
  • Artificial Intelligence 2.5k
  • Computer Vision and Pattern Recognition 1.5k
  • Information Systems 624
  • Media Technology 431
  • Computational Mechanics 333
Replace Qinfeng Shi with:
Qinfeng Shi Australia
Lei Zhu China
Zenglin Xu China
Zhiwen Yu China
Jing Liu China
Jianping Fan China
Mu Li China
Sebastian Nowozin United Kingdom
Yu Xue China
Hau−San Wong Hong Kong
Qinfeng Shi Australia View profile →
Citations per field, relative to Quanming Yao
Quanming Yao · 1×
Citations per year, relative to Quanming Yao
Quanming Yao · 1×

Countries citing papers authored by Quanming Yao

Since Specialization
Citations

This map shows the geographic impact of Quanming Yao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Quanming Yao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quanming Yao more than expected).

Fields of papers citing papers by Quanming Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Quanming Yao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Quanming Yao. The network helps show where Quanming Yao may publish in the future.

Co-authorship network of co-authors of Quanming Yao

This figure shows the co-authorship network connecting the top 25 collaborators of Quanming Yao. A scholar is included among the top collaborators of Quanming Yao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Quanming Yao. Quanming Yao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 1
3 0
4 4
5 3
6 2
7 19
8 3
9
Progressive Feature Interaction Search for Deep Sparse Network
3
10
Efficient Backbone Search for Scene Text Recognition.
7
11
Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering
1
12
Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding
2
13
Differentiable Neural Architecture Search via Proximal Iterations.
3
14
Neural Recurrent Structure Search for Knowledge Graph Embedding.
2
15
Few-shot Learning: A Survey
48
16
Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations
10
17
Privacy-preserving Transfer Learning for Knowledge Sharing.
3
18
Scalable Tensor Completion with Nonconvex Regularization.
2
19
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels breakdown →
664
20
Loss-aware Binarization of Deep Networks
48

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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