Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
This map shows the geographic impact of Tong Zhang'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 Tong Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tong Zhang more than expected).
This network shows the impact of papers produced by Tong Zhang. 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 Tong Zhang. The network helps show where Tong Zhang may publish in the future.
Co-authorship network of co-authors of Tong Zhang
This figure shows the co-authorship network connecting the top 25 collaborators of Tong Zhang.
A scholar is included among the top collaborators of Tong Zhang 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 Tong Zhang. Tong Zhang is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhang, Tong, et al.. (2020). Black-Box Adversarial Attack with Transferable Model-based Embedding. Rare & Special e-Zone (The Hong Kong University of Science and Technology).7 indexed citations
3.
Zhang, Weizhong, et al.. (2020). How to Characterize The Landscape of Overparameterized Convolutional Neural Networks. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 33. 3797–3807.1 indexed citations
Han, Shi, et al.. (2019). Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS. arXiv (Cornell University).8 indexed citations
Wang, Qing, Jiechao Xiong, Lei Han, et al.. (2018). Exponentially Weighted Imitation Learning for Batched Historical Data. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 31. 6288–6297.18 indexed citations
9.
Fang, Meng, Cheng Zhou, Bei Shi, et al.. (2018). DHER: Hindsight Experience Replay for Dynamic Goals. Rare & Special e-Zone (The Hong Kong University of Science and Technology).33 indexed citations
10.
Luo, Wenhan, et al.. (2018). End-to-end Active Object Tracking via Reinforcement Learning. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 7. 3286–3295.15 indexed citations
11.
Johnson, Rie & Tong Zhang. (2018). Composite Functional Gradient Learning of Generative Adversarial Models. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 2371–2379.1 indexed citations
12.
Zhang, Tong, et al.. (2018). Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 31. 8366–8375.7 indexed citations
13.
Zheng, Shun, Jialei Wang, Fen Xia, Wei Xu, & Tong Zhang. (2017). A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 18(115). 1–52.6 indexed citations
14.
Shamir, Ohad, Nati Srebro, & Tong Zhang. (2014). Communication-Efficient Distributed Optimization using an Approximate Newton-type Method. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 32(2). 1000–1008.138 indexed citations
Zhang, Tong. (2005). The Model and the Performance Estimation Index Used for Management Information System.
17.
Ando, Rie Kubota, Mark Dredze, & Tong Zhang. (2005). TREC 2005 genomics track experiments at IBM watson. Rare & Special e-Zone (The Hong Kong University of Science and Technology).16 indexed citations
18.
Meir, Ron & Tong Zhang. (2003). Generalization error bounds for Bayesian mixture algorithms. Journal of Machine Learning Research. 4. 839–860.61 indexed citations
19.
Meir, Ron & Tong Zhang. (2002). Data-Dependent Bounds for Bayesian Mixture Methods. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 15. 335–342.2 indexed citations
20.
Zhang, Tong. (1999). Some Theoretical Results Concerning the Convergence of Compositions of Regularized Linear Functions. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 12. 370–378.1 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.