Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
The general approach for automatically driving data collection using information from previously acquired data is called active learning. Traditional active learning addresses the...
One of the major difficulties in face recognition systems is the in-depth pose variation problem. Most face recognition approaches assume that the pose of the face is known. In th...
Time series data is common in many settings including scientific and financial applications. In these applications, the amount of data is often very large. We seek to support pred...
Abstract. In order to effectively and quickly answer queries in environments with distributed RDF/OWL, we present a query optimization algorithm to identify the potentially relevan...