Pairwise Comparisons with Flexible Time-Dynamics

18 Mar 2019Lucas MaystreVictor KristofMatthias Grossglauser

Inspired by applications in sports where the skill of players or teams competing against each other varies over time, we propose a probabilistic model of pairwise-comparison outcomes that can capture a wide range of time dynamics. We achieve this by replacing the static parameters of a class of popular pairwise-comparison models by continuous-time Gaussian processes; the covariance function of these processes enables expressive dynamics... (read more)

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