This paper highlights the crucial role that modern machine learning techniques can play in the optimization of treatment strategies for patients with chronic disorders. In particu...
Arthur Guez, Robert D. Vincent, Massimo Avoli, Joe...
We address the problem of optimizing the distribution of partially replicated databases over a computer network. Replication is used to increase data availability in the presence ...
Sarah Abdul-Wahid, Razvan Andonie, Joseph Lemley, ...
In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal ...
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...