In this paper, we propose an extended local search framework to solve combinatorial optimization problems with data uncertainty. Our approach represents a major departure from sce...
Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP i...
Evolutionary Algorithms (EAs) have been largely applied to optimisation and synthesis of controllers. In spite of several successful applications and competitive solutions, the st...
The growth of the web has directly influenced the increase in the availability of relational data. One of the key problems in mining such data is computing the similarity between o...
Pradeep Muthukrishnan, Dragomir R. Radev, Qiaozhu ...
We address the problem of fast, large scale sketch-based image retrieval, searching in a database of over one million images. We show that current retrieval methods do not scale w...
Mathias Eitz, Kristian Hildebrand, Tamy Boubekeur,...