Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity

Fariborz Salehi, Ehsan Abbasi, Babak Hassibi. Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity. In Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicolò Cesa-Bianchi, Roman Garnett, editors, Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, 3-8 December 2018, Montréal, Canada. pages 8655-8666, 2018. [doi]

@inproceedings{SalehiAH18-0,
  title = {Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity},
  author = {Fariborz Salehi and Ehsan Abbasi and Babak Hassibi},
  year = {2018},
  url = {http://papers.nips.cc/paper/8082-learning-without-the-phase-regularized-phasemax-achieves-optimal-sample-complexity},
  researchr = {https://researchr.org/publication/SalehiAH18-0},
  cites = {0},
  citedby = {0},
  pages = {8655-8666},
  booktitle = {Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, 3-8 December 2018, Montréal, Canada},
  editor = {Samy Bengio and Hanna M. Wallach and Hugo Larochelle and Kristen Grauman and Nicolò Cesa-Bianchi and Roman Garnett},
}