A Discriminative Latent Variable Model for Online Clustering

Rajhans Samdani, Kai-Wei Chang, and Dan Roth, in ICML, 2014.


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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.

Bib Entry

@inproceedings{samdani2014discriminative,
  author = {Samdani, Rajhans and Chang, Kai-Wei and Roth, Dan},
  title = {A Discriminative Latent Variable Model for Online Clustering},
  booktitle = {ICML},
  slide_url = {/documents/slides/samdani2014discriminative_slide.pdf},
  year = {2014}
}

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