2 papers
cs.LG2019
PROPS: Probabilistic personalization of black-box sequence models
Michael Thomas Wojnowicz, Xuan Zhao
We present PROPS, a lightweight transfer learning mechanism for sequential data. PROPS learns probabilistic perturbations around the predictions of one or more arbitrarily complex,…
stat.ML2019
Projecting "better than randomly": How to reduce the dimensionality of very large datasets in a way that outperforms random projections
Michael Wojnowicz, Di Zhang, Glenn Chisholm +2
For very large datasets, random projections (RP) have become the tool of choice for dimensionality reduction. This is due to the computational complexity of principal component ana…