2 citations · 2 across the 6 of their papers we have counts for
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cs.LG2022★ 2 cited
Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits
Gergely Neu, Julia Olkhovskaya, Matteo Papini +1
We study the Bayesian regret of the renowned Thompson Sampling algorithm in contextual bandits with binary losses and adversarially-selected contexts. We adapt the information-theo…
cs.CV2022
Efficient conditioned face animation using frontally-viewed embedding
Maxime Oquab, Daniel Haziza, Ludovic Schwartz +5
As the quality of few shot facial animation from landmarks increases, new applications become possible, such as ultra low bandwidth video chat compression with a high degree of rea…