Hidden Markov Models (HMMs) are an useful and widely utilized approach to the modeling of data sequences. One of the problems related to this technique is finding the optimal stru...
We propose Action-Reaction Learning as an approach for analyzing and synthesizing human behaviour. This paradigm uncovers causal mappings between past and future events or between...
Minimal perfect hash functions are used for memory efficient storage and fast retrieval of items from static sets. We present an infinite family of efficient and practical algori...
George Havas, Bohdan S. Majewski, Nicholas C. Worm...
Abstract. We present a new approach to biometrics that makes probabilistic inferences about matching without ever estimating an identity "template". The biometric data is...
Simon J. D. Prince, Jania Aghajanian, Umar Mohamme...
The results of the latest International Probabilistic Planning Competition (IPPC-2008) indicate that the presence of dead ends, states with no trajectory to the goal, makes MDPs h...