Several problem in Artificial Intelligence and Pattern Recognition are computationally intractable due to their inherent complexity and the exponential size of the solution space. One example of such problems is biclustering, a specific clustering problem where rows and columns of a data-matrix must be clustered simultaneously. Quantum information processing could provide a viable alternative to combat such a complexity. A notable work in this direction is the recent development of the D-Wave computer, whose processor is able to exploit quantum mechanical effects in order to perform quantum annealing. The question motivating this work is whether the use of this special hardware is a viable approach to efficiently solve the biclustering problem. As a first step towards the solution of this problem, we show a feasible encoding of biclustering into the D-Wave quantum annealing hardware, and provide a theoretical analysis of its correctness.
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