Elisabeth Giem

619 total citations
9 papers, 430 citations indexed

About

Elisabeth Giem is a scholar working on Information Systems, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Elisabeth Giem has authored 9 papers receiving a total of 430 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Information Systems, 4 papers in Computational Theory and Mathematics and 3 papers in Computer Networks and Communications. Recurrent topics in Elisabeth Giem's work include Rough Sets and Fuzzy Logic (4 papers), Data Mining Algorithms and Applications (4 papers) and Distributed systems and fault tolerance (3 papers). Elisabeth Giem is often cited by papers focused on Rough Sets and Fuzzy Logic (4 papers), Data Mining Algorithms and Applications (4 papers) and Distributed systems and fault tolerance (3 papers). Elisabeth Giem collaborates with scholars based in United States, China and Macao. Elisabeth Giem's co-authors include Guoyin Wang, Shuyin Xia, Zizhong Chen, Hao Zhang, Wenhua Li, Xinbo Gao, Deyu Meng, Xiaochuan Dai, Wei Wei and Changqing Zhang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Knowledge and Data Engineering.

In The Last Decade

Elisabeth Giem

9 papers receiving 425 citations

Peers

Elisabeth Giem

AI

CTM

CVPR

IS

SP

Shuxia Lu China

Shangzhu Jin China

Tengyu Yin China

Padmapriya Praveenkumar India

Lanying Wang China

Zhijian Wang China

Yanting Guo China

Debrup Chakraborty India

Binbin Sang China

Jiang Xie China

Shuxia Lu China

Elisabeth Giem

198 ×0.7

AI

96 ×0.5

CTM

114 ×0.7

CVPR

57 ×0.5

IS

24 ×0.6

SP

Citations per year, relative to Elisabeth Giem Elisabeth Giem (= 1×) peers Shuxia Lu

Countries citing papers authored by Elisabeth Giem

Since Specialization

Citations

This map shows the geographic impact of Elisabeth Giem'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 Elisabeth Giem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Elisabeth Giem more than expected).

Fields of papers citing papers by Elisabeth Giem

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Elisabeth Giem. 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 Elisabeth Giem. The network helps show where Elisabeth Giem may publish in the future.

Co-authorship network of co-authors of Elisabeth Giem

This figure shows the co-authorship network connecting the top 25 collaborators of Elisabeth Giem. A scholar is included among the top collaborators of Elisabeth Giem 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 Elisabeth Giem. Elisabeth Giem is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

1.

Zhai, Yujia, Elisabeth Giem, Kai Zhao, et al.. (2023). FT-BLAS: A Fault Tolerant High Performance BLAS Implementation on x86 CPUs. IEEE Transactions on Parallel and Distributed Systems. 34(12). 3207–3223. 1 indexed citations

2.

Xia, Shuyin, Guoyin Wang, Yunlong Cheng, et al.. (2022). An Efficient and Accurate Rough Set for Feature Selection, Classification, and Knowledge Representation. IEEE Transactions on Knowledge and Data Engineering. 35(8). 7724–7735. 39 indexed citations

3.

Xia, Shuyin, Xiaochuan Dai, Guoyin Wang, Xinbo Gao, & Elisabeth Giem. (2022). An Efficient and Adaptive Granular-Ball Generation Method in Classification Problem. IEEE Transactions on Neural Networks and Learning Systems. 35(4). 5319–5331. 69 indexed citations

4.

Bosilca, George, Aurélien Bouteiller, Bogdan Nicolae, et al.. (2022). Integrating process, control-flow, and data resiliency layers using a hybrid Fenix/Kokkos approach. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 418–428. 2 indexed citations

5.

Xia, Shuyin, Shulin Wu, Xinxing Chen, et al.. (2022). GRRS: Accurate and Efficient Neighborhood Rough Set for Feature Selection. IEEE Transactions on Knowledge and Data Engineering. 35(9). 9281–9294. 17 indexed citations

6.

Xia, Shuyin, et al.. (2021). mCRF and mRD: Two Classification Methods Based on a Novel Multiclass Label Noise Filtering Learning Framework. IEEE Transactions on Neural Networks and Learning Systems. 33(7). 2916–2930. 36 indexed citations

7.

Xia, Shuyin, Deyu Meng, Changqing Zhang, et al.. (2020). A Fast Adaptive k-means with No Bounds. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(1). 1–1. 101 indexed citations

8.

Xia, Shuyin, Hao Zhang, Wenhua Li, et al.. (2020). GBNRS: A Novel Rough Set Algorithm for Fast Adaptive Attribute Reduction in Classification. IEEE Transactions on Knowledge and Data Engineering. 34(3). 1231–1242. 159 indexed citations

9.

Li, Sihuan, Xin Liang, Jieyang Chen, et al.. (2019). FT-iSort. 1–17. 6 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.

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