475 citations · 1.8k across the 18 of their papers we have counts for
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cs.LG2020★ 1 cited
Efficient Wasserstein Natural Gradients for Reinforcement Learning
Ted Moskovitz, Michael Arbel, Ferenc Huszar +1
A novel optimization approach is proposed for application to policy gradient methods and evolution strategies for reinforcement learning (RL). The procedure uses a computationally…
cs.LG2020★ 3 cited
Deep Bayesian Bandits: Exploring in Online Personalized Recommendations
Dalin Guo, Sofia Ira Ktena, Ferenc Huszar +3
Recommender systems trained in a continuous learning fashion are plagued by the feedback loop problem, also known as algorithmic bias. This causes a newly trained model to act gree…
cs.LG2014★ 37 cited
Optimally-Weighted Herding is Bayesian Quadrature
Ferenc Huszar, David Duvenaud
Herding and kernel herding are deterministic methods of choosing samples which summarise a probability distribution. A related task is choosing samples for estimating integrals usi…