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I haven't formulated my problem formally yet. But, the goal is to minimize the squared error i.e. $ (L - \sum_{i=1}^{N}{w_{i}l_{i}})^2$ where $l_{i}$ are constants, $w_{i}$ are weights to be optimized. Weight can only take values in binary space i.e. 0/1. Is there any way to run the optimization on these kinds of problems? I understand that I can formulate the constraints in the form $w_{i}(w_{i}-1) = 0$. But, it leads to exponential number of solutions which are intractable when N is very large.

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    There is such a theory, though I don't understand it well enough to post a full answer: http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=E0C7AC3E8A614F3E40BF11201134FEB7?doi=10.1.1.19.4370&rep=rep1&type=pdf2012-04-04

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