8 citations · 13 across the 7 of their papers we have counts for
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cs.LG2020
Learning to Rank under Multinomial Logit Choice
James A. Grant, David S. Leslie
Learning the optimal ordering of content is an important challenge in website design. The learning to rank (LTR) framework models this problem as a sequential problem of selecting…
cs.LG2020
Filtered Poisson Process Bandit on a Continuum
James A. Grant, Roberto Szechtman
We consider a version of the continuum armed bandit where an action induces a filtered realisation of a non-homogeneous Poisson process. Point data in the filtered sample are then…
cs.LG2020★ 3 cited
On Thompson Sampling for Smoother-than-Lipschitz Bandits
James A. Grant, David S. Leslie
Thompson Sampling is a well established approach to bandit and reinforcement learning problems. However its use in continuum armed bandit problems has received relatively little at…