Countries citing papers authored by Xiaoli Z. Fern
Since
Specialization
Citations
This map shows the geographic impact of Xiaoli Z. Fern'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 Xiaoli Z. Fern with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoli Z. Fern more than expected).
This network shows the impact of papers produced by Xiaoli Z. Fern. 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 Xiaoli Z. Fern. The network helps show where Xiaoli Z. Fern may publish in the future.
Co-authorship network of co-authors of Xiaoli Z. Fern
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoli Z. Fern.
A scholar is included among the top collaborators of Xiaoli Z. Fern 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 Xiaoli Z. Fern. Xiaoli Z. Fern is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Fern, Alan, et al.. (2021). An Empirical Study of Bayesian Optimization: Acquisition Versus Partition. Journal of Machine Learning Research. 22(4). 1–25.2 indexed citations
Fern, Xiaoli Z., et al.. (2018). Joint Neural Entity Disambiguation with Output Space Search. International Conference on Computational Linguistics. 2170–2180.1 indexed citations
6.
Li, Fuxin, et al.. (2017). FILTER SHAPING FOR CONVOLUTIONAL NEURAL NETWORKS. International Conference on Learning Representations.11 indexed citations
7.
Ma, Chao, et al.. (2017). Multi-Task Structured Prediction for Entity Analysis: Search-Based Learning Algorithms. Asian Conference on Machine Learning. 514–529.2 indexed citations
Raich, Raviv, et al.. (2015). Multi-instance multi-label learning in the presence of novel class instances. UCrea (University of Cantabria). 2427–2435.37 indexed citations
10.
Jalali, Ali, Javad Azimi, & Xiaoli Z. Fern. (2012). Exploration vs Exploitation in Bayesian Optimization. arXiv (Cornell University).6 indexed citations
Azimi, Javad, Alan Fern, & Xiaoli Z. Fern. (2011). Budgeted Optimization with Concurrent Stochastic-Duration Experiments. Neural Information Processing Systems. 24. 1098–1106.6 indexed citations
13.
Doppa, Janardhan Rao, et al.. (2011). Inverting Grice's Maxims to Learn Rules from Natural Language Extractions. Neural Information Processing Systems. 24. 1053–1061.11 indexed citations
14.
Doppa, Janardhan Rao, et al.. (2011). Learning Rules from Incomplete Examples via Implicit Mention Models. Asian Conference on Machine Learning. 197–212.4 indexed citations
15.
Doppa, Janardhan Rao, et al.. (2010). Towards learning rules from natural texts. North American Chapter of the Association for Computational Linguistics. 70–77.4 indexed citations
16.
Azimi, Javad, Alan Fern, & Xiaoli Z. Fern. (2010). Batch Bayesian Optimization via Simulation Matching. Neural Information Processing Systems. 23. 109–117.40 indexed citations
17.
Azimi, Javad & Xiaoli Z. Fern. (2009). Adaptive cluster ensemble selection. International Joint Conference on Artificial Intelligence. 992–997.73 indexed citations
18.
Fern, Xiaoli Z. & Carla E. Brodley. (2006). Cluster Ensembles for High Dimensional Clustering: An Empirical Study.20 indexed citations
19.
Fern, Xiaoli Z. & Carla E. Brodley. (2003). Boosting lazy decision trees. International Conference on Machine Learning. 178–185.11 indexed citations
20.
Fern, Xiaoli Z. & Carla E. Brodley. (2003). Random projection for high dimensional data clustering: a cluster ensemble approach. International Conference on Machine Learning. 186–193.379 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.