153 citations · 860 across the 45 of their papers we have counts for
4 papers · 1 filter
Antithetic and Monte Carlo kernel estimators for partial rankings
Maria Lomeli, Mark Rowland, Arthur Gretton +1
In the modern age, rankings data is ubiquitous and it is useful for a variety of applications such as recommender systems, multi-object tracking and preference learning. However, m…
Gaussian Process Behaviour in Wide Deep Neural Networks
Alexander G. de G. Matthews, Mark Rowland, Jiri Hron +2
Whilst deep neural networks have shown great empirical success, there is still much work to be done to understand their theoretical properties. In this paper, we study the relation…
Structured Evolution with Compact Architectures for Scalable Policy Optimization
Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani +2
We present a new method of blackbox optimization via gradient approximation with the use of structured random orthogonal matrices, providing more accurate estimators than baselines…
An Analysis of Categorical Distributional Reinforcement Learning
Mark Rowland, Marc G. Bellemare, Will Dabney +2
Distributional approaches to value-based reinforcement learning model the entire distribution of returns, rather than just their expected values, and have recently been shown to yi…