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Fine-Grained Complexity 1

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Fine-grained complexity pins concrete running-time hypotheses (SETH: no 2^{n(1−ε)} SAT, 3SUM: no n^{2−o(1)}, APSP: no n^{3−o(1)}) and proves many practical problems hard by tight reductions. The key reduction splits SAT variables in half, encodes each half-assignment as a binary vector and produces 2^{n/2} vectors of m+2 dimensions so that an orthogonal pair exists iff the formula is satisfiable; thus a sub-n^2 algorithm for Orthogonal Vectors would refute SETH on the word RAM model.

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  1. 0:00Fine-grained complexity intro
  2. 10:49Traditional hardness limits
  3. 16:16Fine-grained approach
  4. 29:21Fine-grained reductions
  5. 36:30APSP reductions
  6. 42:30SETH to OV reduction
  7. 52:56Open questions
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