Qiang Liu

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Qiang Liu
Assistant Professor
Computer Science
Dartmouth College
Qiang.Liu(at)dartmouth.edu
Office: Sudikoff 209
Phone: 603-646-8747

("Qiang" sounds like "Chee-ah-ng", and "Liu" as "l-yo")


New. PhD positions at Dartmouth are available. Please email me if interested.

Research

My research area is machine learning and statistics, with interests spreading over the pipeline of data collection (e.g., by crowdsourcing), learning, inference, decision making, and various applications using probabilistic modeling.

Examples of topics of interest: probabilistic graphical models; variational and Monte Carlo inference; deep learning; distributed learning; big data problems; kernel and nonparametric methods; applications: crowdsourcing, vision, bioinformatics, etc.

I am an action editor of Journal of Machine Learning Research (JMLR).

See the homepage of my group for more information.

Teaching

  • CS74/174: Machine Learning and Statistic Analysis, Spring 2017

  • CS70/170: Numerical and Computational Tools for Applied Science, Fall 2016

  • CS89/189: Advanced Topics in Machine Learning, Winter 2016 [syllabus]

  • CS74/174: Machine Learning and Statistic Analysis, Spring 2016 [page, canvas]

PhD Students

<Click for my Group Page>

Selected / Recent Publications and Slides

<Click for the Full List>

New. Probabilistic Learning and Inference Using Stein’s Method [Project Page, slides]

Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning

Wang, Liu; preprint 2016 [code]

Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm

Liu, Wang; NIPS, 2016 (to appear). [code]

A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation

Liu, Lee, Jordan; ICML, 2016. [code: matlab, R ]

Distributed Estimation, Information Loss and Exponential Families

Liu, Ihler; Advances in Neural Information Processing Systems (NIPS) 2014.

Reasoning and Decisions in Probabilistic Graphical Models - A Unified Framework

Liu; PhD Thesis, Fall 2014

Variational Algorithms for Marginal MAP

Liu, Ihler; Journal of Machine Learning Research (JMLR) 2013.

Variational Inference for Crowdsourcing

Liu, Peng, Ihler; Advances in Neural Information Processing Systems (NIPS) 2012. [Appendix, Code]