Label Ranking Methods based on the Plackett-Luce Model

112 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Calibrated Fairness in Bandits (2017, neutral): “To be concrete, we adopt the Placke-Luce (PL) model [1, 8], where every arm i is parameterized by a quality parameter, νi ∈ R+, such that”
KDGAN: Knowledge Distillation with Generative Adversarial Networks (2018, methodology): “Following existing work [29], we use multi-label learning problems [12, 18, 53] as the target application scenarios of our methods for illustration purpose.”
Learning Scoring Functions with Order-Preserving Losses and Standardized Supervision (2011, methodology): “This constraint is similar to the Plackett-Luce model (up to the possibility of assigning a probability of 0 to some permutations), for which consistency w.r.t. the 0 / 1-error was also pointed out by (Cheng et al., 2010).”