NIPS Proceedingsβ

Xinhua Zhang

13 Papers

  • Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction (2017)
  • Decomposition-Invariant Conditional Gradient for General Polytopes with Line Search (2017)
  • Convex Two-Layer Modeling with Latent Structure (2016)
  • Convex Deep Learning via Normalized Kernels (2014)
  • Robust Bayesian Max-Margin Clustering (2014)
  • Convex Two-Layer Modeling (2013)
  • Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space (2013)
  • Polar Operators for Structured Sparse Estimation (2013)
  • Accelerated Training for Matrix-norm Regularization: A Boosting Approach (2012)
  • Convex Multi-view Subspace Learning (2012)
  • Lower Bounds on Rate of Convergence of Cutting Plane Methods (2010)
  • Kernel Measures of Independence for non-iid Data (2008)
  • Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms (2006)