Automated Feature Learning
Automated Feature Learning is a computational methodology within the field of machine learning that systematically discovers and extracts relevant patterns or representations from raw data without human intervention, distinguishing itself by its reliance on algorithmic inference rather than manual feature engineering.
286
Publications
17.2K
Citations
1K
Authors
467
Institutions
Publications per year
2017–2026
199
Parents
286
Manish Motwani, Damini Dey, Daniel S. Berman et al. · European Heart Journal · 2016 · 705 citations · Full text
Medicine, Cardiology, Radiology +17
Automatically learning semantic features for defect prediction
Song Wang, Taiyue Liu, Lin Tan · 2016 · 692 citations
1–5 of 286
1K
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King Mongkut's University of Technology North Bangkok, Thailand
3 publications · 386 citations
3
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1–5 of 1K
467
Stanford University
Stanford, United States
11 h-index
23 publications
3.6K citations
Dalian University of Technology
Dalian, China
4 h-index
9 publications
810 citations
Nanyang Technological University
Singapore, Singapore
4 h-index
10 publications
627 citations

Victoria University of Wellington
Wellington, New Zealand
4 h-index
12 publications
1.1K citations

University of Edinburgh
Edinburgh, United Kingdom
4 h-index
9 publications
497 citations

Southeast University
Nanjing, China
4 h-index
15 publications
499 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
3 h-index
2 publications
56 citations

University of Ottawa
Ottawa, Canada
3 h-index
5 publications
857 citations
1–8 of 467
Repository · 15 publications · 972 citations
13
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6 publications · 274 citations
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5 publications · 275 citations
5
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4 publications · 534 citations
5
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TKDE · 3 publications · 974 citations
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