1 citations · 2 across the 2 of their papers we have counts for
3 papers
stat.ML2020
Compressing Large Sample Data for Discriminant Analysis
Alexander F. Lapanowski, Irina Gaynanova
Large-sample data became prevalent as data acquisition became cheaper and easier. While a large sample size has theoretical advantages for many statistical methods, it presents com…
stat.ML2019★ 1 cited
Sparse Feature Selection in Kernel Discriminant Analysis via Optimal Scoring
Alexander F. Lapanowski, Irina Gaynanova
We consider the two-group classification problem and propose a kernel classifier based on the optimal scoring framework. Unlike previous approaches, we provide theoretical guarante…
cs.IT2012★ 1 cited
One-bit compressed sensing with non-Gaussian measurements
Albert Ai, Alex Lapanowski, Yaniv Plan +1
In one-bit compressed sensing, previous results state that sparse signals may be robustly recovered when the measurements are taken using Gaussian random vectors. In contrast to st…