NIPS Proceedingsβ

Mark Schmidt

6 Papers

  • Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates (2019)
  • SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient (2018)
  • StopWasting My Gradients: Practical SVRG (2015)
  • A Stochastic Gradient Method with an Exponential Convergence _Rate for Finite Training Sets (2012)
  • Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization (2011)
  • An interior-point stochastic approximation method and an L1-regularized delta rule (2008)