Sanaa Chafik

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The running time of the classical algorithms of the Markov Decision Process (MDP) typically grows linearly with the state space size, which makes them frequently intractable. This paper presents a Modified Policy Iteration algorithm to compute an optimal policy for large Markov decision processes in the discounted reward criteria and under infinite horizon.(More)
Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest Neighbours search problem in high dimensional space. Euclidean LSH is the most popular variation of LSH that has been successfully applied in many multimedia applications. However, the Euclidean LSH presents limitations that affect search performances. The main(More)
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