Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
Existing Database Management Systems (DBMSs) do not handle efficiently multi-dimensional data such as boxes, polygons, or even points in a multi-dimensional space. We examine acc...
Approximate linear programming (ALP) has emerged recently as one of the most promising methods for solving complex factored MDPs with finite state spaces. In this work we show th...
This paper presents a grounded theory of information sharing behavior of the users of a personal learning space. A personal learning space is an environment consisted of weblog, e...
In previous work, singular points (or top points) in the scale space representation of generic images have proven valuable for image matching. In this paper, we propose a construct...
Bram Platel, M. Fatih Demirci, Ali Shokoufandeh, L...