A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent

Ben London. A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent. In Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, Roman Garnett, editors, Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 4-9 December 2017, Long Beach, CA, USA. pages 2935-2944, 2017. [doi]

@inproceedings{London17,
  title = {A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent},
  author = {Ben London},
  year = {2017},
  url = {http://papers.nips.cc/paper/6886-a-pac-bayesian-analysis-of-randomized-learning-with-application-to-stochastic-gradient-descent},
  researchr = {https://researchr.org/publication/London17},
  cites = {0},
  citedby = {0},
  pages = {2935-2944},
  booktitle = {Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 4-9 December 2017, Long Beach, CA, USA},
  editor = {Isabelle Guyon and Ulrike von Luxburg and Samy Bengio and Hanna M. Wallach and Rob Fergus and S. V. N. Vishwanathan and Roman Garnett},
}