Fei Sha

19.0k citations

218 papers · 9.0k indexed · 5 hit papers · h-index 42

Impact in

Computer Vision and Pattern Recognition top 0.2%
- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Face and Expression Recognition
- Human Pose and Action Recognition
Artificial Intelligence top 0.1%
- Domain Adaptation and Few-Shot Learning
- Topic Modeling
- Machine Learning and ELM
- Natural Language Processing Techniques

Papers in ⓘ

Computer Vision and Pattern Recognition 52
- Multimodal Machine Learning Applications 20
- Advanced Image and Video Retrieval Techniques 19
Artificial Intelligence 79
- Domain Adaptation and Few-Shot Learning 29
- Topic Modeling 18
- Natural Language Processing Techniques 16

Co-authors: Kristen Grauman (13 shared papers)Boqing Gong (8 shared papers)Fernando Pereira (1 shared paper)Yuan Shi (3 shared papers)Lawrence K. Saul (14 shared papers)Kilian Q. Weinberger (9 shared papers)Hexiang Hu (12 shared papers)Han-Jia Ye (3 shared papers)
Journals: Construction and Building Materials (15 papers)Case Studies in Construction Materials (6 papers)Journal of Materials Research and Technology (4 papers)Ocean Engineering (3 papers)Research in Nondestructive Evaluation (3 papers)
Partner nations: China United States United Kingdom

In The Last Decade

Fei Sha

200 papers receiving 8.5k citations

Hit Papers

5 papers align trajectories log scale

WeatherBench 2: A Benchmark for the Next Generation of Data‐Driven Global Weather Models 2024 · 82 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2024 Journal of Advances in Modeling Earth Systems
2020 Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions
2012 Geodesic flow kernel for unsupervised domain adaptation
2012 arXiv (Cornell University)
2003 Shallow parsing with conditional random fields

Peers

Countries citing papers authored by Fei Sha

Since Specialization

Citations

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

Fields of papers citing papers by Fei Sha

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Fei Sha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Fei Sha Line = papers co-authored together Fei Sha links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Showing the 20 most-cited of 218 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Geodesic flow kernel for unsupervised domain adaptation Boqing Gong, Yuan Shi, Fei Sha, Kristen Grauman Hit paper breakdown →	2012	1488
2	Shallow parsing with conditional random fields Fei Sha, Fernando Pereira Hit paper breakdown →	2003	847
3	Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions Han-Jia Ye, Hexiang Hu, De‐Chuan Zhan, Fei Sha Hit paper breakdown →	2020	451
4	Marginalized Denoising Autoencoders for Domain Adaptation arXiv (Cornell University) ·Minmin Chen, Zhixiang Xu, Kilian Q. Weinberger, Fei Sha Hit paper breakdown →	2012	344
5	Learning a kernel matrix for nonlinear dimensionality reduction Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul	2004	309
6	Connecting the Dots with Landmarks: Discriminatively Learning Domain-Invariant Features for Unsupervised Domain Adaptation International Conference on Machine Learning ·Boqing Gong, Kristen Grauman, Fei Sha	2013	277
7	DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification Simon Lacoste-Julien, Fei Sha, Michael I. Jordan	2008	237
8	Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification Andrea Frome, Yoram Singer, Fei Sha, Jitendra Malik	2007	229
9	Investigation of fundamental EMI source mechanisms driving common-mode radiation from printed circuit boards with attached cables IEEE Transactions on Electromagnetic Compatibility ·D.M. Hockanson, James L. Drewniak, T.H. Hubing, T.P. Van Doren, Fei Sha, Michael J. Wilhelm	1996	218
10	Diverse Sequential Subset Selection for Supervised Video Summarization Neural Information Processing Systems ·Boqing Gong, Wei‐Lun Chao, Kristen Grauman, Fei Sha	2014	215
11	Learning with Whom to Share in Multi-task Feature Learning International Conference on Machine Learning ·Zhuoliang Kang, Kristen Grauman, Fei Sha	2011	175
12	Experimental study on performance of cement-based grouts admixed with fly ash, bentonite, superplasticizer and water glass Construction and Building Materials ·Fei Sha, Shucai Li, Rentai Liu, Zhaofeng Li, Qingsong Zhang	2017	146
13	Deformable Spatial Pyramid Matching for Fast Dense Correspondences Jaechul Kim, Ce Liu, Fei Sha, Kristen Grauman	2013	143
14	Active learning for accelerated design of layered materials npj Computational Materials ·Lindsay Bassman Oftelie, Pankaj Rajak, Rajiv K. Kalia, Aiichiro Nakano, Fei Sha, Jifeng Sun, David J. Singh, Muratahan Aykol, Patrick Huck, Kristin A. Persson, Priya Vashishta	2018	130
15	Aligning Where to See and What to Tell: Image Captioning with Region-Based Attention and Scene-Specific Contexts IEEE Transactions on Pattern Analysis and Machine Intelligence ·Kun Fu, Junqi Jin, Runpeng Cui, Fei Sha, Changshui Zhang	2016	125
16	Attention Correctness in Neural Image Captioning Proceedings of the AAAI Conference on Artificial Intelligence ·Chenxi Liu, Junhua Mao, Fei Sha, Alan Yuille	2017	124
17	Multiplicative Updates for Nonnegative Quadratic Programming Neural Computation ·Fei Sha, Yuanqing Lin, Lawrence K. Saul, Daniel D. Lee	2007	114
18	Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines ScholarlyCommons (University of Pennsylvania) ·Fei Sha, Lawrence K. Saul, Daniel D. Lee	2002	101
19	Non-linear Metric Learning neural information processing systems ·Dor Kedem, Stephen Tyree, Fei Sha, Gert Lanckriet, Kilian Q. Weinberger	2012	99
20	Sharing features between objects and their attributes Scholarworks@UNIST (Ulsan National Institute of Science and Technology) ·Sung Ju Hwang, Fei Sha, Kristen Grauman	2011	86

About Fei Sha

Fei Sha is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Civil and Structural Engineering, Environmental Engineering and Signal Processing, having authored 218 papers that have together received 9.0k indexed citations. Recurring topics across this work include Grouting, Rheology, and Soil Mechanics (29 papers), Domain Adaptation and Few-Shot Learning (29 papers), Microbial Applications in Construction Materials (23 papers), Concrete and Cement Materials Research (22 papers), Multimodal Machine Learning Applications (20 papers), Advanced Image and Video Retrieval Techniques (19 papers), Topic Modeling (18 papers) and Natural Language Processing Techniques (16 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (3.6k citations), Artificial Intelligence (4.9k citations), Signal Processing (791 citations), Media Technology (367 citations) and Civil and Structural Engineering (892 citations). Fei Sha has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Kristen Grauman, Boqing Gong, Fernando Pereira, Yuan Shi, Lawrence K. Saul, Kilian Q. Weinberger, Hexiang Hu, Han-Jia Ye, De‐Chuan Zhan and Michael I. Jordan. Their work appears in journals such as Construction and Building Materials, Case Studies in Construction Materials, Journal of Materials Research and Technology, Ocean Engineering and Research in Nondestructive Evaluation.

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.

Explore authors with similar magnitude of impact