Statistics and Data Science Seminar
Dongxiao Zhu
Wayne State University
Model-based approaches to learn partitions from data
Abstract: In multi-class classification, different classes may relate to different feature groups. In this
talk, I will present a class-conditional regularization of the multinomial logistic model to enable the
discovery of class-specific feature groups. I will also present an efficient cyclic block coordinate descent
based algorithm to solve the model. In another work, I will introduce a novel joint mixture model framework
to estimate cluster size distribution, particularly for over-dispersed (high variance) ones, together with
cluster compactness (density). Our methods are sufficiently flexible and general to be applied to multiple
application domains, such as social networks, image segmentation, natural language processing and
bioinformatics.
Wednesday October 19, 2016 at 3:00 PM in SEO 636