3 papers
stat.ME2026
A reduced rank model for spatial categorical data with many classes
Paul B May, Andrew Simpson, Semhar Michael
We develop an identifiable reduced-rank spatial multinomial model for categorical data with many classes. The model represents class-specific spatial effects through a low-dimensio…
stat.CO2026
Estimation of Parameters of the Truncated Normal Distribution with Unknown Bounds
Dylan Borchert, Semhar Michael, Christopher Saunders
Estimators of parameters of truncated distributions, namely the truncated normal distribution, have been widely studied for a known truncation region. There is also literature for…
stat.ME2025
Statistical few-shot learning for large-scale classification via parameter pooling
Andrew Simpson, Semhar Michael
In large-scale few-shot learning for classification problems, often there are a large number of classes and few high-dimensional observations per class. Previous model-based method…