This map shows the geographic impact of Hsiang‐Fu 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 Hsiang‐Fu Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hsiang‐Fu Yu more than expected).
This network shows the impact of papers produced by Hsiang‐Fu 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 Hsiang‐Fu Yu. The network helps show where Hsiang‐Fu Yu may publish in the future.
Co-authorship network of co-authors of Hsiang‐Fu Yu
This figure shows the co-authorship network connecting the top 25 collaborators of Hsiang‐Fu Yu.
A scholar is included among the top collaborators of Hsiang‐Fu 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 Hsiang‐Fu Yu. Hsiang‐Fu Yu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Xiong, Yuanhao, Wei-Cheng Chang, Cho‐Jui Hsieh, Hsiang‐Fu Yu, & Inderjit S. Dhillon. (2022). Extreme Zero-Shot Learning for Extreme Text Classification. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 5455–5468.7 indexed citations
4.
Chen, Patrick, Hsiang‐Fu Yu, Inderjit S. Dhillon, & Cho‐Jui Hsieh. (2021). DRONE: Data-aware Low-rank Compression for Large NLP Models. Neural Information Processing Systems. 34.14 indexed citations
Shen, Yanyao, Hsiang‐Fu Yu, Sujay Sanghavi, & Inderjit S. Dhillon. (2020). Extreme Multi-label Classification from Aggregated Labels. International Conference on Machine Learning. 1. 8752–8762.1 indexed citations
7.
Chang, Wei-Cheng, Hsiang‐Fu Yu, Kai Zhong, Yiming Yang, & Inderjit S. Dhillon. (2019). X-BERT: eXtreme Multi-label Text Classification with BERT. arXiv (Cornell University).5 indexed citations
8.
Yu, Hsiang‐Fu, et al.. (2019). A Fast Sampling Algorithm for Maximum Inner Product Search. International Conference on Artificial Intelligence and Statistics. 3004–3012.8 indexed citations
9.
Chang, Wei-Cheng, Hsiang‐Fu Yu, Kai Zhong, Yiming Yang, & Inderjit S. Dhillon. (2019). A Modular Deep Learning Approach for Extreme Multi-label Text Classification.. arXiv (Cornell University).7 indexed citations
10.
Chang, Wei-Cheng, Hsiang‐Fu Yu, Kai Zhong, Yiming Yang, & Inderjit S. Dhillon. (2019). X-BERT: eXtreme Multi-label Text Classification with using Bidirectional Encoder Representations from Transformers.14 indexed citations
11.
Zhang, Jiong, et al.. (2019). Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models. 935–943.1 indexed citations
12.
Yu, Hsiang‐Fu, Cho‐Jui Hsieh, Qi Lei, & Inderjit S. Dhillon. (2017). A Greedy Approach for Budgeted Maximum Inner Product Search. Neural Information Processing Systems. 30. 5453–5462.10 indexed citations
13.
Yu, Hsiang‐Fu, Nikhil Rao, & Inderjit S. Dhillon. (2016). Temporal regularized matrix factorization for high-dimensional time series prediction. Neural Information Processing Systems. 29. 847–855.215 indexed citations
14.
You, Yang, Xiangru Lian, Ji Liu, et al.. (2016). Asynchronous Parallel Greedy Coordinate Descent. Neural Information Processing Systems. 29. 4682–4690.15 indexed citations
Yu, Hsiang‐Fu, Hung-Yi Lo, Hsun-Ping Hsieh, et al.. (2010). Feature Engineering and Classifier Ensemble for KDD Cup 2010. Knowledge Discovery and Data Mining.89 indexed citations
19.
Lo, Hung-Yi, Kai‐Wei Chang, Shang-Tse Chen, et al.. (2009). An ensemble of three classifiers for KDD cup 2009: expanded linear model, heterogeneous boosting, and selective naïve Bayes. Knowledge Discovery and Data Mining. 57–64.11 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.