On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms

Shalev-Shwartz and Singer. "On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms." Annual Conference on Computational Learning Theory, 2008. doi:10.1007/s10994-010-5173-z

[Shalev-Shwartz and Singer. "On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms." Annual Conference on Computational Learning Theory, 2008.](https://mlanthology.org/colt/2008/shalevshwartz2008colt-equivalence/) doi:10.1007/s10994-010-5173-z

@inproceedings{shalevshwartz2008colt-equivalence,
  title     = {{On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms}},
  author    = {Shalev-Shwartz, Shai and Singer, Yoram},
  booktitle = {Annual Conference on Computational Learning Theory},
  year      = {2008},
  pages     = {311-322},
  doi       = {10.1007/s10994-010-5173-z},
  url       = {https://mlanthology.org/colt/2008/shalevshwartz2008colt-equivalence/}
}