Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes. Ashtiani, H., Ben-David, S., Harvey, N. J. A., Liaw, C., Mehrabian, A., & Plan, Y. In Bengio, S., Wallach, H. M., Larochelle, H., Grauman, K., Cesa-Bianchi, N., & Garnett, R., editors, Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada, pages 3416–3425, 2018.
Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes [link]Paper  bibtex   
@inproceedings{DBLP:conf/nips/AshtianiBHLMP18,
  author    = {Hassan Ashtiani and
               Shai Ben{-}David and
               Nicholas J. A. Harvey and
               Christopher Liaw and
               Abbas Mehrabian and
               Yaniv Plan},
  editor    = {Samy Bengio and
               Hanna M. Wallach and
               Hugo Larochelle and
               Kristen Grauman and
               Nicol{\`{o}} Cesa{-}Bianchi and
               Roman Garnett},
  title     = {Nearly tight sample complexity bounds for learning mixtures of Gaussians
               via sample compression schemes},
  booktitle = {Advances in Neural Information Processing Systems 31: Annual Conference
               on Neural Information Processing Systems 2018, NeurIPS 2018, December
               3-8, 2018, Montr{\'{e}}al, Canada},
  pages     = {3416--3425},
  year      = {2018},
  url       = {https://proceedings.neurips.cc/paper/2018/hash/70ece1e1e0931919438fcfc6bd5f199c-Abstract.html},
  timestamp = {Thu, 21 Jan 2021 15:15:20 +0100},
  biburl    = {https://dblp.org/rec/conf/nips/AshtianiBHLMP18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

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