Cross-platform Predictive Modeling
Cross-Platform Predictive Modeling is a computational framework that integrates and analyzes behavioral, contextual, and temporal data across multiple digital platforms to generate anticipatory insights about user actions, preferences, or system dynamics by leveraging machine learning algorithms trained on harmonized cross-environmental datasets.
7
Publications
269
Citations
30
Authors
12
Institutions
Publications per year
2017–2026
6
Parents
7
Collaborative learning between cloud and end devices
Yan Lu, Yuanchao Shu, Xu Tan et al. · 2019 · 33 citations
1–5 of 7
30
2
h-index
1
h-index
1
h-index
1
h-index
1
h-index
1–5 of 30
12
Tsinghua University
Beijing, China
3 h-index
6 publications
299 citations
Microsoft Research Asia (China)
Beijing, China
2 h-index
4 publications
204 citations
Keck Hospital of USC
Los Angeles, United States
1 h-index
3 publications
132 citations
Microsoft Research (United Kingdom)
Cambridge, United Kingdom
1 h-index
5 publications
165 citations

University of Waterloo
Waterloo, Canada
1 h-index
4 publications
232 citations
The University of Texas at Austin
Austin, United States
1 h-index
3 publications
60 citations
Microsoft (United States)
Redmond, United States
1 h-index
1 publications
33 citations
New York University
New York, United States
1 h-index
1 publications
33 citations
1–8 of 12
1 publications · 12 citations
1
h-index
1 publications · 20 citations
1
h-index
Conference · 1 publications · 62 citations
1
h-index
1 publications · 44 citations
1
h-index
TIST · 1 publications · 40 citations
1
h-index
1–5