This map shows the geographic impact of Felix X. Yu'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 Felix X. Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Felix X. Yu more than expected).
This network shows the impact of papers produced by Felix X. Yu. 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 Felix X. Yu. The network helps show where Felix X. Yu may publish in the future.
Co-authorship network of co-authors of Felix X. Yu
This figure shows the co-authorship network connecting the top 25 collaborators of Felix X. Yu.
A scholar is included among the top collaborators of Felix X. Yu 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 Felix X. Yu. Felix X. Yu 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
1.
Reddi, Sashank J., Rama Kumar Pasumarthi, Aditya Krishna Menon, et al.. (2021). RankDistil: Knowledge Distillation for Ranking. International Conference on Artificial Intelligence and Statistics. 2368–2376.4 indexed citations
2.
Liu, Yuhan, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, & Michael Riley. (2020). Learning discrete distributions: user vs item-level privacy. arXiv (Cornell University). 33. 20965–20976.
3.
Yu, Felix X., Ankit Singh Rawat, Aditya Krishna Menon, & Sanjiv Kumar. (2020). Federated Learning with Only Positive Labels. International Conference on Machine Learning. 1. 10946–10956.1 indexed citations
4.
Yao, Tiansheng, Xinyang Yi, Derek Zhiyuan Cheng, et al.. (2020). Self-supervised Learning for Deep Models in Recommendations.. arXiv (Cornell University).20 indexed citations
5.
Wu, Shanshan, Alexandros G. Dimakis, Sujay Sanghavi, et al.. (2018). The Sparse Recovery Autoencoder.. arXiv (Cornell University).3 indexed citations
6.
Yen, Ian En-Hsu, Satyen Kale, Felix X. Yu, et al.. (2018). Loss Decomposition for Fast Learning in Large Output Spaces.. International Conference on Machine Learning. 5626–5635.3 indexed citations
7.
Wu, Xiang, Ruiqi Guo, Ananda Theertha Suresh, et al.. (2017). Multiscale Quantization for Fast Similarity Search. Neural Information Processing Systems. 30. 5745–5755.27 indexed citations
8.
Yu, Felix X., Ananda Theertha Suresh, Krzysztof Choromański, Daniel Holtmann-Rice, & Sanjiv Kumar. (2016). Orthogonal Random Features. arXiv (Cornell University). 29. 1975–1983.29 indexed citations
Pennington, Jeffrey, Felix X. Yu, & Sanjiv Kumar. (2015). Spherical Random Features for polynomial kernels. Neural Information Processing Systems. 28. 1846–1854.21 indexed citations
11.
Cheng, Yu, Felix X. Yu, Rogério Feris, et al.. (2015). Fast Neural Networks with Circulant Projections.. arXiv (Cornell University).16 indexed citations
Yu, Felix X., Dong Liu, Sanjiv Kumar, Tony Jebara, & Shih‐Fu Chang. (2013). SVM for learning with label proportions. International Conference on Machine Learning.50 indexed citations
17.
Brown, Lisa M., Liangliang Cao, Yu Cheng, et al.. (2013). IBM Research and Columbia University TRECVID-2013 Multimedia Event Detection (MED), Multimedia Event Recounting (MER), Surveillance Event Detection (SED), and Semantic Indexing (SIN) Systems..5 indexed citations
18.
Cao, Liangliang, Shih-Fu Chang, Noel Codella, et al.. (2012). IBM Research and Columbia University TRECVID-2012 Multimedia Event Detection (MED), Multimedia Event Recounting (MER), and Semantic Indexing (SIN) Systems. TRECVID.11 indexed citations
19.
Ji, Rongrong, Felix X. Yu, Tongtao Zhang, & Shih‐Fu Chang. (2012). Active query sensing. ACM Transactions on Multimedia Computing Communications and Applications. 8(3s). 1–21.2 indexed citations
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.