NIPS Proceedingsβ

Kevin Scaman

6 Papers

  • Theoretical Limits of Pipeline Parallel Optimization and Application to Distributed Deep Learning (2019)
  • KONG: Kernels for ordered-neighborhood graphs (2018)
  • Lipschitz regularity of deep neural networks: analysis and efficient estimation (2018)
  • Optimal Algorithms for Non-Smooth Distributed Optimization in Networks (2018)
  • Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks (2015)
  • Tight Bounds for Influence in Diffusion Networks and Application to Bond Percolation and Epidemiology (2014)