NIPS Proceedingsβ

Quanquan Gu

10 Papers

  • Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization (2018)
  • Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization (2018)
  • Stochastic Nested Variance Reduced Gradient Descent for Nonconvex Optimization (2018)
  • Third-order Smoothness Helps: Faster Stochastic Optimization Algorithms for Finding Local Minima (2018)
  • Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimization (2017)
  • Semiparametric Differential Graph Models (2016)
  • High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality (2015)
  • Robust Tensor Decomposition with Gross Corruption (2014)
  • Sparse PCA with Oracle Property (2014)
  • Selective Labeling via Error Bound Minimization (2012)