Affi nity propagation (AP) was recently introduced as an unsupervised learning algorithm for exemplar-based clustering. We present a deriva- tion of AP that is much simpler than the original one and is based on a quite different graphical model. The new model allows easy derivations of message updates for extensions and modifi cations of the standard AP algorithm.We demonstrate this by adjusting the new AP model to repre- sent the capacitated clustering problem. For those wishing to investigate or extend the graphical model of the AP algorithm, we suggest using this new formulation since it allows a simpler and more intuitive model manipulation.

Anity Propagation.pdf

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