Eric F. Lock
@elock.bsky.social
Biostatistician at University of Minnesota
Reposted by Eric F. Lock
F mechanisms (New and Competitive renewals)
Oof!
3/n
Oof!
3/n
March 29, 2025 at 12:58 PM
F mechanisms (New and Competitive renewals)
Oof!
3/n
Oof!
3/n
Reposted by Eric F. Lock
NIH Reporter data through this morning (grants funded up to March 8th)
First, new and competitive renewal grants...
2/n
First, new and competitive renewal grants...
2/n
March 15, 2025 at 4:28 PM
NIH Reporter data through this morning (grants funded up to March 8th)
First, new and competitive renewal grants...
2/n
First, new and competitive renewal grants...
2/n
For estimating low-rank signal in a matrix:
-Nuclear norm (NN) penalization over-shrinks when the signal-to-noise ratio is high 🙁,
-Hard thresholding (HT) the singular values over-fits when the signal-to-noise ratio is low 😲,
-But an empirical variational Bayes (EVB) approach is just right 😎.
-Nuclear norm (NN) penalization over-shrinks when the signal-to-noise ratio is high 🙁,
-Hard thresholding (HT) the singular values over-fits when the signal-to-noise ratio is low 😲,
-But an empirical variational Bayes (EVB) approach is just right 😎.
November 19, 2024 at 3:37 PM
For estimating low-rank signal in a matrix:
-Nuclear norm (NN) penalization over-shrinks when the signal-to-noise ratio is high 🙁,
-Hard thresholding (HT) the singular values over-fits when the signal-to-noise ratio is low 😲,
-But an empirical variational Bayes (EVB) approach is just right 😎.
-Nuclear norm (NN) penalization over-shrinks when the signal-to-noise ratio is high 🙁,
-Hard thresholding (HT) the singular values over-fits when the signal-to-noise ratio is low 😲,
-But an empirical variational Bayes (EVB) approach is just right 😎.