A Discriminative Latent Variable Model for Online Clustering
Venue
International Conference on Machine Learning (2014) (to appear)
Publication Year
2014
Authors
Rajhans Samdani, Kai-Wei Chang, Dan Roth
BibTeX
Abstract
This paper presents a latent variable structured prediction model for
discriminative supervised clustering of items called the Latent Left-linking Model
(L3M). We present an online clustering algorithm for L3M based on a feature-based
item similarity function. We provide a learning framework for estimating the
similarity function and present a fast stochastic gradient-based learning
technique. In our experiments on coreference resolution and document clustering,
L3M outperforms several existing online as well as batch supervised clustering
techniques.
