NIPS2016 Accepted Paper List DeepNLP AI Robotic and STEM Top Conference & Journal Papers

Introduction

Conference NIPS2016 accepted paper complete List. Top ranking conferences for AI and Robotics communities. Total Accepted Paper Count 2

NIPS2016 ACCEPTED PAPER LIST

A Stein variational Newton method

Gianluca Detommaso,Tiangang Cui,Youssef Marzouk,Alessio Spantini,Robert Scheichl

Stein variational gradient descent (SVGD) was recently proposed as a general purpose nonparametric variational inference algorithm: it minimizes the Kullbacku2013Leibler divergence between the target distribution and its approximation by implementing a form of functional gradient descent on a reproducing kernel Hilbert space [Liu & Wang, NIPS 2016]. In this paper, we accelerate and generalize the SVGD algorithm by including second-order information, thereby approximating a Newton-like iteration in function space. We also show how second-order information can lead to more effective choices of kernel. We observe significant computational gains over the original SVGD algorithm in multiple test cases.