NIPS Proceedingsβ

Eric P. Xing

10 Papers

  • Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices (2016)
  • Stochastic Variational Deep Kernel Learning (2016)
  • Variance Reduction in Stochastic Gradient Langevin Dynamics (2016)
  • The Human Kernel (2015)
  • Dependent nonparametric trees for dynamic hierarchical clustering (2014)
  • On Model Parallelization and Scheduling Strategies for Distributed Machine Learning (2014)
  • A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks (2013)
  • More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server (2013)
  • Restricting exchangeable nonparametric distributions (2013)
  • Variance Reduction for Stochastic Gradient Optimization (2013)