Complexity Theoretic Limitations on Learning DNF's

نویسندگان

  • Amit Daniely
  • Shai Shalev-Shwartz
چکیده

Using the recently developed framework of [14], we show that under a natural assumption on the complexity of refuting random K-SAT formulas, learning DNF formulas is hard. Furthermore, the same assumption implies the hardness of learning intersections of ω(log(n)) halfspaces, agnostically learning conjunctions, as well as virtually all (distribution free) learning problems that were previously shown hard (under complexity assumptions). ∗Dept. of Mathematics, The Hebrew University, Jerusalem, Israel †School of Computer Science and Engineering, The Hebrew University, Jerusalem, Israel

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تاریخ انتشار 2016