: In many computer vision classification problems, both the error and time characterizes the quality of a decision. We show that such problems can be formalized in the framework of...
We present a learning framework for Markovian decision processes that is based on optimization in the policy space. Instead of using relatively slow gradient-based optimization al...
We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...
We present a tool deciding a fragment of set theory. It is designed to be easily accessible via the internet and intuitively usable by anyone who is working with sets to describe a...
Many solutions for securing inter-provider handover proposed to date make use of the concept of security context transfer. However, none of these solutions addresses problems aris...