Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
We introduce cube summing, a technique that permits dynamic programming algorithms for summing over structures (like the forward and inside algorithms) to be extended with non-loc...
Server-side programming is one of the key technologies that support today's WWW environment. It makes it possible to generate Web pages dynamically according to a user's...
The Dynamic Spatial Approximation Tree (dsa–tree) is a recently proposed data structure for searching in metric spaces. It has been shown that it compares favorably against alte...