Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
The rapid increase in the data volumes for the past few decades has intensified the need for high processing power for database and data mining applications. Researchers have acti...
Anastassia Ailamaki, Naga K. Govindaraju, Dinesh M...
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
This paper reports work to support dependability arguments about the future reliability of a product before there is direct empirical evidence. We develop a method for estimating ...
Background: Many bioinformatics applications rely on controlled vocabularies or ontologies to consistently interpret and seamlessly integrate information scattered across public r...
Irena Spasic, Daniel Schober, Susanna-Assunta Sans...