Using a combination of machine learning probabilistic tools, we have shown that some chemistry students fail to develop productive problem solving strategies through practice alon...
Ron Stevens, Amy Soller, Alessandra Giordani, Luca...
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
This paper exploits the spatial representation of state space problem graphs to preprocess and enhance heuristic search engines. It combines classical AI exploration with computati...
We present a method for nonrigid registration of 2-D geometric shapes. Our contribution is twofold. First, we extend the classic chamfer-matching energy to a variational functional...
PLAN is a language designed for programming active networks, and can more generally be regarded as a model of mobile computation. PLAN generalizes the paradigm of imperative funct...