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We present sum-set inequalities specialized to the generalized degrees of freedom (GDoF) framework. These are information theoretic lower bounds on the entropy of bounded density linear combinations of discrete, power-limited dependent random variables in terms of the joint entropies of arbitrary linear combinations of new random variables that are obtained by power level partitioning of the original random variables. These bounds generalize the aligned image sets approach, and are usefuldoi:10.1109/isit.2017.8006615 dblp:conf/isit/DavoodiJ17 fatcat:w2ms22xfwfb5lhuoyo6mglhcwq