Daniel D. Lee

135 papers receiving 17.8k citations

Daniel D. Lee's Hit Papers

Grassmann discriminant analysis 2008 · 467 citations
4670+9+18Years since publication2.5k5.0k7.5k

Peers

Daniel D. Lee
Comparison fields: 5 of 210
  • Computational Mathematics 561
  • Signal Processing 3.7k
  • Computer Vision and Pattern Recognition 6.4k
  • Media Technology 1.5k
  • Artificial Intelligence 5.3k
Replace Jieping Ye with:
Jieping Ye United States
H. Sebastian Seung United States
Chris Ding United States
Vin de Silva United States
Partha Niyogi United States
Heng Huang United States
Lawrence K. Saul United States
Alexander J. Smola United States
Xiaofei He China
Sam T. Roweis Canada
Daniel D. Lee relative to Jieping Ye United States Jieping Ye's profile →
Citations per field
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Citations per year

Countries citing papers authored by Daniel D. Lee

Since Specialization
Citations

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

Fields of papers citing papers by Daniel D. Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel D. Lee. 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 Daniel D. Lee. The network helps show where Daniel D. Lee may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel D. Lee, 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 Daniel D. Lee Line = papers co-authored together Daniel D. Lee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 137 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Learning the parts of objects by non-negative matrix factorization
Hit paper breakdown →
19999927
2
Algorithms for Non-negative Matrix Factorization
Hit paper breakdown →
20004353
3
Grassmann discriminant analysis
Hit paper breakdown →
2008467
4 2004387
5 2000273
6 2001230
7 2006202
8
Semisupervised alignment of manifolds.
2005195
9 2019174
10 2018141
11 2007127
12 2004121
13
Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines
2002114
14 200090
15 202090
16
The Rectified Gaussian Distribution
199784
17 202078
18
Unsupervised Learning by Convex and Conic Coding
199675
19
Learning High Dimensional Correspondences from Low Dimensional Manifolds
200363
20 201157

About Daniel D. Lee

Daniel D. Lee is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering, Control and Systems Engineering and Aerospace Engineering, having authored 137 papers that have together received 18.6k indexed citations. Recurring topics across this work include Robotic Locomotion and Control (26 papers), Neural Networks and Applications (22 papers), Robotics and Sensor-Based Localization (20 papers), Prosthetics and Rehabilitation Robotics (20 papers), Robotic Path Planning Algorithms (19 papers), Robot Manipulation and Learning (19 papers), Face and Expression Recognition (15 papers) and Blind Source Separation Techniques (14 papers). The work is most often cited by research in Computational Mathematics (561 citations), Signal Processing (3.7k citations), Computer Vision and Pattern Recognition (6.4k citations), Media Technology (1.5k citations) and Artificial Intelligence (5.3k citations). Daniel D. Lee has collaborated with scholars based in United States, South Korea and Israel. Frequent co-authors include H. Sebastian Seung, Jihun Hamm, Lawrence K. Saul, Jihun Ham, Haim Sompolinsky, Fei Sha, Bernhard Schölkopf, Sebastian Mika, David W. Tank and Ben Y. Reis. Their work appears in journals such as Neural Computation, Physical Review Letters, Applied Physics B, IEEE Robotics and Automation Letters and Journal of Field Robotics.

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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