Cross-Platform Feature Alignment is a methodological framework in cross-platform analytics that enables the integration and harmonization of heterogeneous feature representations across diverse digital platforms by establishing semantic correspondences and structural equivalences to support unified data analysis.
4
Publications
115
Citations
16
Authors
12
Institutions
Publications per year
2017–2026
2
Parents
Publications
4
Improving cross-platform binary analysis using representation learning via graph alignment
Geunwoo Kim, Sanghyun Hong, Michael Franz et al. · 2022 · 26 citations
CHAOS: Composable Highly Accurate OS-based power models
John D. Davis, Suzanne Rivoire, Moisés Goldszmidt et al. · 2012 · 17 citations
1–4 of 4
Authors
16
- SH
1
h-index
- SR
1
h-index
- JW
1
h-index
- SR
1
h-index
- MF
1
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1–5 of 16
Institutions
12
Georgia Institute of Technology
Atlanta, United States
1 h-index
2 publications
28 citations
University of California, Santa Cruz
Santa Cruz, United States
1 h-index
1 publications
17 citations
Microsoft (United States)
Redmond, United States
1 h-index
2 publications
34 citations
Yonsei University
Seoul, South Korea
1 h-index
1 publications
26 citations
National University of Singapore
Singapore, Singapore
1 h-index
1 publications
58 citations
Oregon State University
Corvallis, United States
1 h-index
1 publications
26 citations
Sonoma State University
Rohnert Park, United States
1 h-index
1 publications
17 citations
Hefei General Machinery Research Institute (China)
Hefei, China
1 h-index
1 publications
58 citations
1–8 of 12
Venues
- IEEE/ASME Transactions on Mechatronics
1 publications · 58 citations
1
h-index
1–1