Séminaire IPI : « Hybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference Aggregation »
30 novembre 2018 @ 15 h 00 min - 16 h 00 min
Le prochain séminaire de l’équipe IPI aura lieu vendredi 30 novembre de 15h à 16h à Polytech, en salle D010 du bâtiment IRESTE.
L’orateur est Jing Li, post-doc au sein de l’équipe et qui abordera, en Anglais, le thème suivant : Hybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference Aggregation.
The next IPI seminar will held on Friday the 30th of November (3pm-4pm), in room D010 in Ireste Building at Polytech’Nantes.
The speaker will be Dr Jing Li who is postdoc in the IPI team.
Hybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference Aggregation
In this talk, a hybrid active sampling strategy for pairwise preference aggregation is presented, which aims at recovering the underlying rating of the test candidates from sparse and noisy pairwise labeling. This method employs Bayesian optimization framework and Bradley-Terry model to construct the utility function, then to obtain the Expected Information Gain (EIG) of each pair. For computational efficiency, Gaussian-Hermite quadrature is used for estimation of EIG. In this work, a hybrid active sampling strategy is proposed, either using Global Maximum (GM) EIG sampling or Minimum Spanning Tree (MST) sampling in each trial, which is determined by the test budget. The proposed method has been validated on both simulated and real-world datasets, where it shows higher preference aggregation ability than the state-of-the-art methods.