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A Discriminative Latent Variable Model for Online Clustering
Authors: Rajhans Samdani, Kai-wei Chang and Dan Roth
Conference: Proceedings of the 31st International Conference on Machine Learning (ICML-14)
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, L3 M outperforms several existing online as well as batch supervised clustering techniques.
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