Collaborative Research: High-Dimensional Tensor Learning under Labeled-Data Scarcity — NSF Award to New York University (NY, $87,0
This project harnesses the power of multi-dimensional tensor data to improve predictive accuracy and insights across crucial scientific and societal sectors through the development of advanced tensor classification techniques. Specifically, these techniques will facilitate early Alzheimer's diagnosis via sophisticated
| Award title | Collaborative Research: High-Dimensional Tensor Learning under Labeled-Data Scarcity |
|---|---|
| Award ID | 2412577 |
| Awardee | New York University |
| City | NEW YORK |
| State | NY |
| Amount obligated | $87,026 |
| Principal investigator | Elynn Chen |
| Program | STATISTICS |
| Start date | 09/01/2024 |
| Abstract | This project harnesses the power of multi-dimensional tensor data to improve predictive accuracy and insights across crucial scientific and societal sectors through the development of advanced tensor classification techniques. Specifically, these techniques will facilitate early Alzheimer's diagnosis via sophisticated fMRI tensor analysis and improve the detection of anomalies in complex financial transactions. Despite the richness of tensor data, a significant barrier exists due to the scarcity |
| Source | NSF Awards |
$799/mo
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