10 citations · 10 across the 4 of their papers we have counts for
5 papers
Entropy Regularized Reinforcement Learning with Cascading Networks
Riccardo Della Vecchia, Alena Shilova, Philippe Preux +1
Deep Reinforcement Learning (Deep RL) has had incredible achievements on high dimensional problems, yet its learning process remains unstable even on the simplest tasks. Deep RL us…
Convex Optimization with an Interpolation-based Projection and its Application to Deep Learning
Riad Akrour, Asma Atamna, Jan Peters
Convex optimizers have known many applications as differentiable layers within deep neural architectures. One application of these convex layers is to project points into a convex…
An Upper Bound of the Bias of Nadaraya-Watson Kernel Regression under Lipschitz Assumptions
Samuele Tosatto, Riad Akrour, Jan Peters
The Nadaraya-Watson kernel estimator is among the most popular nonparameteric regression technique thanks to its simplicity. Its asymptotic bias has been studied by Rosenblatt in 1…
Compatible Natural Gradient Policy Search
Joni Pajarinen, Hong Linh Thai, Riad Akrour +2
Trust-region methods have yielded state-of-the-art results in policy search. A common approach is to use KL-divergence to bound the region of trust resulting in a natural gradient…
APRIL: Active Preference-learning based Reinforcement Learning
Riad Akrour, Marc Schoenauer, Michèle Sebag
This paper focuses on reinforcement learning (RL) with limited prior knowledge. In the domain of swarm robotics for instance, the expert can hardly design a reward function or demo…