Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
Volunteer distributed computations utilize spare processor cycles of personal computers that are connected to the Internet. The related computation integrity concerns are commonly...
In a data word or a data tree each position carries a label from a finite alphabet and a data value from an infinite domain. Over data words we consider the logic LTL↓ 1(F), th...
Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...
Background: The fingerprint of a molecule is a bitstring based on its structure, constructed such that structurally similar molecules will have similar fingerprints. Molecular fin...
Thomas G. Kristensen, Jesper Nielsen, Christian N....