233 citations · 531 across the 34 of their papers we have counts for
5 papers · 1 filter
Improving Offline Contextual Bandits with Distributional Robustness
Otmane Sakhi, Louis Faury, Flavian Vasile
This paper extends the Distributionally Robust Optimization (DRO) approach for offline contextual bandits. Specifically, we leverage this framework to introduce a convex reformulat…
BLOB : A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals
Otmane Sakhi, Stephen Bonner, David Rohde +1
A common task for recommender systems is to build a pro le of the interests of a user from items in their browsing history and later to recommend items to the user from the same ca…
Reconsidering Analytical Variational Bounds for Output Layers of Deep Networks
Otmane Sakhi, Stephen Bonner, David Rohde +1
The combination of the re-parameterization trick with the use of variational auto-encoders has caused a sensation in Bayesian deep learning, allowing the training of realistic gene…
Relaxed Softmax for learning from Positive and Unlabeled data
Ugo Tanielian, Flavian Vasile
In recent years, the softmax model and its fast approximations have become the de-facto loss functions for deep neural networks when dealing with multi-class prediction. This loss…
Distributionally Robust Counterfactual Risk Minimization
Louis Faury, Ugo Tanielian, Flavian Vasile +2
This manuscript introduces the idea of using Distributionally Robust Optimization (DRO) for the Counterfactual Risk Minimization (CRM) problem. Tapping into a rich existing literat…