• Corpus ID: 219531142

Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Connections to Evolvability

  title={Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Connections to Evolvability},
  author={Sitan Chen and Frederic Koehler and Ankur Moitra and Morris Yau},
In this paper we revisit some classic problems on classification under misspecification. In particular, we study the problem of learning halfspaces under Massart noise with rate $\eta$. In a recent work, Diakonikolas, Goulekakis, and Tzamos resolved a long-standing problem by giving the first efficient algorithm for learning to accuracy $\eta + \epsilon$ for any $\epsilon > 0$. However, their algorithm outputs a complicated hypothesis, which partitions space into $\text{poly}(d,1/\epsilon… 

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