NIPS Proceedingsβ

Tuo Zhao

13 Papers

  • Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization (2018)
  • Provable Gaussian Embedding with One Observation (2018)
  • The Physical Systems Behind Optimization Algorithms (2018)
  • Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization (2018)
  • Deep Hyperspherical Learning (2017)
  • On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning (2017)
  • Parametric Simplex Method for Sparse Learning (2017)
  • NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization (2016)
  • A Nonconvex Optimization Framework for Low Rank Matrix Estimation (2015)
  • Accelerated Mini-batch Randomized Block Coordinate Descent Method (2014)
  • Multivariate Regression with Calibration (2014)
  • Sparse Inverse Covariance Estimation with Calibration (2013)
  • Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation (2012)