We initiate the study of the compressibility of NP problems. We
consider NP problems that have long instances but relatively
short witnesses. The question is, can one efficiently compress an
instance and store a shorter representation that maintains the
information of whether the original input is in the language or
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Ramsey theory assures us that in any graph there is a clique or independent set of a certain size, roughly logarithmic in the graph size. But how difficult is it to find the clique or independent set? If the graph is given explicitly, then it is possible to do so ... more >>>

We present a worst case decoding problem whose hardness reduces to that of solving the Learning Parity with Noise (LPN) problem, in some parameter regime. Prior to this work, no worst case hardness result was known for LPN (as opposed to syntactically similar problems such as Learning with Errors). The ... more >>>