Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Talk Slides

less than 1 minute read

Published:

First post of the year :-) Following are two talks I gave in the seminar with topic machine learning.

Fixed Points of SVGD

1 minute read

Published:

The following note is inspired by the discussion on properties of linear kernel functions. Though they’re not supposed to perform well when we use SVGD, they could provide exact estimates for some functions including the mean and variance. Three kinds of kernel functions, constant kernel, linear kernel and polynomial kernel respectively, are explored here to see what kinds of functions they could provide exact estimates for and to see how well particles could approximate the target distribution.

Reading: Stein method in machine learning

4 minute read

Published:

Reading notes for paper Stein variational gradient descent: A general purpose bayesian inference algorithm. (Liu & Wang, 2016) including introduction to Stein’s identity, Stein discrepancy and finally Stein variational gradient descent.

portfolio

publications

Structured Stein Variational Inference for Continuous Graphical Models

Published in Arxiv, 2017

We propose a novel distributed inference algorithm for continuous graphical models by extending Stein variational gradient descent (SVGD) to leverage the Markov dependency structure of the distribution of interest.

D. Wang∗, Z. Zeng∗, and Q. Liu. Structured Stein Variational Inference for Continuous Graphical Models. ArXiv e-prints, November 2017. (∗Equal contribution, will submit to ICML 18) https://arxiv.org/abs/1711.07168

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.