Plackett-Luce Networks for Dyad Ranking

We propose a new method for dyad ranking, a problem that was recently introduced in the realm of preference learning. Our method, called PLNet, combines a statistical model for rank data, namely the Plackett-Luce model, with neural networks (feed-forward multi-layer perceptrons) in order to learn joint-feature representations for dyads, which are pairs of objects from two domains. The efficacy of PLNet is shown by comparing it experimentally with state-of-the-art methods for dyad and label ranking.